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b/LLM-Zero-shot_approach/TryingPrompts.ipynb |
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"execution_count": 5, |
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"metadata": { |
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"colab": { |
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"base_uri": "https://localhost:8080/" |
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"id": "34gu2GrcsT7A", |
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"outputId": "27d1602c-1a99-407a-cbe3-ee010186558c" |
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}, |
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"outputs": [ |
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{ |
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"name": "stdout", |
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"output_type": "stream", |
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"text": [ |
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" Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", |
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" Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", |
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" Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", |
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" Building wheel for transformers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", |
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m105.0/105.0 MB\u001b[0m \u001b[31m9.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", |
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"\u001b[?25h Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", |
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" Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", |
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" Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", |
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m279.7/279.7 kB\u001b[0m \u001b[31m5.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", |
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"\u001b[?25h Building wheel for peft (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", |
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" Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", |
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" Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", |
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" Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", |
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" Building wheel for accelerate (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", |
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m116.3/116.3 kB\u001b[0m \u001b[31m14.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", |
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m134.8/134.8 kB\u001b[0m \u001b[31m18.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", |
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"\u001b[?25h\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", |
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"ibis-framework 7.1.0 requires pyarrow<15,>=2, but you have pyarrow 15.0.0 which is incompatible.\u001b[0m\u001b[31m\n", |
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"\u001b[0m" |
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] |
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} |
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], |
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"source": [ |
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"!pip install -q -U git+https://github.com/huggingface/transformers.git\n", |
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"!pip install -q -U bitsandbytes\n", |
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"!pip install -q -U git+https://github.com/huggingface/peft.git\n", |
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"!pip install -q -U git+https://github.com/huggingface/accelerate.git\n", |
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"!pip install -q trl" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 6, |
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"metadata": { |
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"id": "77V6IkhFw_aC" |
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}, |
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"outputs": [], |
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"source": [ |
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"from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig\n", |
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"import torch" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 7, |
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"metadata": { |
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"id": "eV2tAB_-w1_V" |
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}, |
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"outputs": [], |
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"source": [ |
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"model_name = \"mistralai/Mistral-7B-v0.1\"" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 8, |
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"metadata": { |
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"colab": { |
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"base_uri": "https://localhost:8080/", |
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"/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n", |
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"The secret `HF_TOKEN` does not exist in your Colab secrets.\n", |
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"To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n", |
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"You will be able to reuse this secret in all of your notebooks.\n", |
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"Please note that authentication is recommended but still optional to access public models or datasets.\n", |
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"output_type": "display_data" |
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{ |
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"data": { |
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"application/vnd.jupyter.widget-view+json": { |
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"model_id": "0b51ac305a5a4cc08b5041aab7a4398d", |
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"version_major": 2, |
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"version_minor": 0 |
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}, |
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"output_type": "display_data" |
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} |
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], |
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"source": [ |
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"# Load base model(Mistral 7B)\n", |
|
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"bnb_config = BitsAndBytesConfig(\n", |
|
|
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" load_in_4bit= True,\n", |
|
|
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" bnb_4bit_quant_type= \"nf4\",\n", |
|
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" bnb_4bit_compute_dtype= torch.bfloat16,\n", |
|
|
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" bnb_4bit_use_double_quant= False,\n", |
|
|
284 |
")\n", |
|
|
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"model = AutoModelForCausalLM.from_pretrained(\n", |
|
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" model_name,\n", |
|
|
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" quantization_config=bnb_config,\n", |
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" device_map={\"\": 0}\n", |
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")" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 9, |
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"metadata": { |
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"colab": { |
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"base_uri": "https://localhost:8080/", |
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"height": 163, |
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"referenced_widgets": [ |
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] |
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}, |
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"id": "laX7-Z55xj4e", |
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"outputId": "29a39867-2838-45a0-aea1-65d83c0a1146" |
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}, |
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"outputs": [ |
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{ |
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"data": { |
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"application/vnd.jupyter.widget-view+json": { |
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"model_id": "e19528df413c4447ba8fc82cc5b943c6", |
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"version_major": 2, |
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"version_minor": 0 |
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"output_type": "display_data" |
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{ |
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"data": { |
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"application/vnd.jupyter.widget-view+json": { |
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"model_id": "4430c6d824624517b3aee0c8494a3bcc", |
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"version_major": 2, |
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"version_minor": 0 |
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}, |
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"output_type": "display_data" |
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{ |
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"application/vnd.jupyter.widget-view+json": { |
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"model_id": "edf6db440c7f421ba11c4fccc75b4d59", |
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"version_major": 2, |
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"version_minor": 0 |
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}, |
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"output_type": "display_data" |
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}, |
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{ |
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"data": { |
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"application/vnd.jupyter.widget-view+json": { |
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"model_id": "7daa3ea916c34dff90928c76774123d1", |
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"version_major": 2, |
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"version_minor": 0 |
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] |
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}, |
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"output_type": "display_data" |
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}, |
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{ |
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"data": { |
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"text/plain": [ |
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"(True, True)" |
|
|
410 |
] |
|
|
411 |
}, |
|
|
412 |
"execution_count": 9, |
|
|
413 |
"metadata": {}, |
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|
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"output_type": "execute_result" |
|
|
415 |
} |
|
|
416 |
], |
|
|
417 |
"source": [ |
|
|
418 |
"tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)\n", |
|
|
419 |
"tokenizer.padding_side = 'left'\n", |
|
|
420 |
"tokenizer.pad_token = tokenizer.eos_token\n", |
|
|
421 |
"tokenizer.add_eos_token = True\n", |
|
|
422 |
"tokenizer.add_bos_token, tokenizer.add_eos_token" |
|
|
423 |
] |
|
|
424 |
}, |
|
|
425 |
{ |
|
|
426 |
"cell_type": "code", |
|
|
427 |
"execution_count": 10, |
|
|
428 |
"metadata": { |
|
|
429 |
"id": "qmc6FBvnxn66" |
|
|
430 |
}, |
|
|
431 |
"outputs": [], |
|
|
432 |
"source": [ |
|
|
433 |
"from transformers import TextGenerationPipeline" |
|
|
434 |
] |
|
|
435 |
}, |
|
|
436 |
{ |
|
|
437 |
"cell_type": "code", |
|
|
438 |
"execution_count": 11, |
|
|
439 |
"metadata": { |
|
|
440 |
"id": "V69mfDEfxwS9" |
|
|
441 |
}, |
|
|
442 |
"outputs": [], |
|
|
443 |
"source": [ |
|
|
444 |
"pipe = TextGenerationPipeline(model = model, tokenizer = tokenizer)" |
|
|
445 |
] |
|
|
446 |
}, |
|
|
447 |
{ |
|
|
448 |
"cell_type": "code", |
|
|
449 |
"execution_count": 16, |
|
|
450 |
"metadata": { |
|
|
451 |
"id": "_v5brEzC0qzP" |
|
|
452 |
}, |
|
|
453 |
"outputs": [], |
|
|
454 |
"source": [ |
|
|
455 |
"prompt = '''I need to perform a named entity recognition task on a text related with inclusion criteria in clinical trials.\n", |
|
|
456 |
"The entities you need to recognize are: Condition, Value, Drug, Procedure, Measurement, Temporal, Observation, Person, Mood, Device and Pregnancy_considerations.\n", |
|
|
457 |
"Particularly you have to produce the ouput in the BIO format. I will show you an example of the expected output.\n", |
|
|
458 |
"Input text: Patients with symptomatic CNS metastases or leptomeningeal involvement\n", |
|
|
459 |
"Output:\n", |
|
|
460 |
"Patients O\n", |
|
|
461 |
"with O\n", |
|
|
462 |
"symptomatic O\n", |
|
|
463 |
"CNS B-Condition\n", |
|
|
464 |
"metastases I-Condition\n", |
|
|
465 |
"or O\n", |
|
|
466 |
"leptomeningeal B-Condition\n", |
|
|
467 |
"involvement I-Condition\n", |
|
|
468 |
"\n", |
|
|
469 |
"You can see that tokens without any entity are labeled as O, and the tokens that are part of an entity are labeled as B-<entity> or I-<entity> depending on if they are the beginning or the inside of the entity.\n", |
|
|
470 |
"Please, just answer the question for this specific example and stop writting after that.\n", |
|
|
471 |
"Input text: Patients who are eligible for coronary revascularization ( angioplasty or CABG )\n", |
|
|
472 |
"Output:'''" |
|
|
473 |
] |
|
|
474 |
}, |
|
|
475 |
{ |
|
|
476 |
"cell_type": "code", |
|
|
477 |
"execution_count": 37, |
|
|
478 |
"metadata": { |
|
|
479 |
"colab": { |
|
|
480 |
"base_uri": "https://localhost:8080/" |
|
|
481 |
}, |
|
|
482 |
"id": "6NcQ_wuHuKNy", |
|
|
483 |
"outputId": "b5a7d2a2-c0e5-4d11-d7c8-afbe8a98b111" |
|
|
484 |
}, |
|
|
485 |
"outputs": [ |
|
|
486 |
{ |
|
|
487 |
"name": "stderr", |
|
|
488 |
"output_type": "stream", |
|
|
489 |
"text": [ |
|
|
490 |
"Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n" |
|
|
491 |
] |
|
|
492 |
}, |
|
|
493 |
{ |
|
|
494 |
"name": "stdout", |
|
|
495 |
"output_type": "stream", |
|
|
496 |
"text": [ |
|
|
497 |
"\n", |
|
|
498 |
"Patients O\n", |
|
|
499 |
"who O\n", |
|
|
500 |
"are O\n", |
|
|
501 |
"eligible B-Condition\n", |
|
|
502 |
"for B-Condition\n", |
|
|
503 |
"coronary B-Condition\n", |
|
|
504 |
"revascularization I-Condition\n", |
|
|
505 |
"( I-Condition\n", |
|
|
506 |
"angioplasty I-Condition\n", |
|
|
507 |
"or I-Condition\n", |
|
|
508 |
"CABG I-Condition\n", |
|
|
509 |
") I-Condition\n", |
|
|
510 |
"\n", |
|
|
511 |
"Input text: Patients with symptomatic CNS metastases or leptomeningeal involvement\n", |
|
|
512 |
"Output:\n", |
|
|
513 |
"Patients O\n", |
|
|
514 |
"with O\n", |
|
|
515 |
"symptomatic O\n", |
|
|
516 |
"CNS B-Condition\n", |
|
|
517 |
"metastases I-Condition\n", |
|
|
518 |
"or O\n", |
|
|
519 |
"leptomeningeal B-Condition\n", |
|
|
520 |
"involvement I-Condition\n", |
|
|
521 |
"\n", |
|
|
522 |
"Input text: Patients with symptomatic CNS metastases or leptomeningeal involvement\n", |
|
|
523 |
"Output:\n", |
|
|
524 |
"Patients O\n", |
|
|
525 |
"with O\n", |
|
|
526 |
"symptomatic O\n", |
|
|
527 |
"CNS B-Condition\n", |
|
|
528 |
"metastases I-Condition\n", |
|
|
529 |
"or O\n", |
|
|
530 |
"leptomeningeal B-Condition\n", |
|
|
531 |
"involvement I-Condition\n", |
|
|
532 |
"\n", |
|
|
533 |
"Input text: Patients with symptomatic CNS metastases or leptomeningeal involvement\n", |
|
|
534 |
"Output:\n", |
|
|
535 |
"Patients O\n", |
|
|
536 |
"with O\n", |
|
|
537 |
"symptomatic O\n", |
|
|
538 |
"CNS B-Condition\n", |
|
|
539 |
"metastases I-Condition\n", |
|
|
540 |
"or O\n", |
|
|
541 |
"leptomeningeal B-Condition\n", |
|
|
542 |
"involvement I-Condition\n", |
|
|
543 |
"\n", |
|
|
544 |
"Input text: Patients with symptomatic CNS metastases or leptomeningeal involvement\n", |
|
|
545 |
"Output:\n", |
|
|
546 |
"Patients O\n", |
|
|
547 |
"with O\n", |
|
|
548 |
"symptomatic O\n", |
|
|
549 |
"CNS B-Condition\n", |
|
|
550 |
"metastases I-Condition\n", |
|
|
551 |
"or O\n", |
|
|
552 |
"leptomeningeal B-Condition\n", |
|
|
553 |
"involvement I-Condition\n", |
|
|
554 |
"\n", |
|
|
555 |
"Input text: Patients with symptomatic CNS metastases or leptomeningeal involvement\n", |
|
|
556 |
"Output:\n", |
|
|
557 |
"Patients O\n", |
|
|
558 |
"with O\n", |
|
|
559 |
"symptomatic O\n", |
|
|
560 |
"CNS B-Condition\n", |
|
|
561 |
"metastases I-Condition\n", |
|
|
562 |
"or O\n", |
|
|
563 |
"leptomeningeal B-Condition\n", |
|
|
564 |
"involvement I-Condition\n", |
|
|
565 |
"\n", |
|
|
566 |
"Input text: Patients with symptomatic CNS metastases or leptomeningeal involvement\n", |
|
|
567 |
"Output:\n", |
|
|
568 |
"Patients O\n", |
|
|
569 |
"with O\n", |
|
|
570 |
"symptomatic O\n", |
|
|
571 |
"CNS B-Condition\n", |
|
|
572 |
"metastases I-Condition\n", |
|
|
573 |
"or O\n", |
|
|
574 |
"leptomeningeal B-Condition\n", |
|
|
575 |
"involvement\n" |
|
|
576 |
] |
|
|
577 |
} |
|
|
578 |
], |
|
|
579 |
"source": [ |
|
|
580 |
"print(pipe(prompt, max_new_tokens = 500, return_full_text = False, handle_long_generation = \"hole\")[0]['generated_text'])" |
|
|
581 |
] |
|
|
582 |
}, |
|
|
583 |
{ |
|
|
584 |
"cell_type": "code", |
|
|
585 |
"execution_count": 25, |
|
|
586 |
"metadata": { |
|
|
587 |
"id": "oTZQmXt_41MC" |
|
|
588 |
}, |
|
|
589 |
"outputs": [], |
|
|
590 |
"source": [ |
|
|
591 |
"prompt_new = '''I am working on a named entity recognition problem, in the context of clinical\n", |
|
|
592 |
"trials eligibility criteria. I will show you the list of entities:\n", |
|
|
593 |
"- Condition\n", |
|
|
594 |
"- Value\n", |
|
|
595 |
"- Drug\n", |
|
|
596 |
"- Procedure\n", |
|
|
597 |
"- Measurement\n", |
|
|
598 |
"- Temporal\n", |
|
|
599 |
"- Observation\n", |
|
|
600 |
"- Person\n", |
|
|
601 |
"- Mood\n", |
|
|
602 |
"- Device\n", |
|
|
603 |
"\n", |
|
|
604 |
"Your task consists in annotate the named entities in a given sentence in the format I will explain you.\n", |
|
|
605 |
"I will explain you with some examples:\n", |
|
|
606 |
"\n", |
|
|
607 |
"Example 1:\n", |
|
|
608 |
"Input: Patients who have received prior chemotherapy for unresectable disease.\n", |
|
|
609 |
"Output: Patients who have received prior <Procedure>chemotherapy</Procedure> for <Condition>unresectable disease</Condition>.\n", |
|
|
610 |
"\n", |
|
|
611 |
"Example 2:\n", |
|
|
612 |
"Input: Patients with any other severe concurrent disease, which in the judgment of the investigator, would make the patient inappropriate for entry into this study.\n", |
|
|
613 |
"Ouput: Patients with any other severe <Condition>concurrent disease</Condition>, which in the judgment of the investigator, would make the patient <Mood>inappropriate for <Observation>entry into this study</Observation>.\n", |
|
|
614 |
"\n", |
|
|
615 |
"As you can see, in each example, the extracted entities are enclosed using the sintax: <ENT>text of the entity</ENT>.\n", |
|
|
616 |
"\n", |
|
|
617 |
"Please now annotate as explained before the following sentence:\n", |
|
|
618 |
"\n", |
|
|
619 |
"Input: Have had one prior platinum-based chemotherapy regimen for the treatment of primary disease.\n", |
|
|
620 |
"Output:'''" |
|
|
621 |
] |
|
|
622 |
}, |
|
|
623 |
{ |
|
|
624 |
"cell_type": "code", |
|
|
625 |
"execution_count": 26, |
|
|
626 |
"metadata": { |
|
|
627 |
"colab": { |
|
|
628 |
"base_uri": "https://localhost:8080/" |
|
|
629 |
}, |
|
|
630 |
"id": "PSKPRzwm5HAG", |
|
|
631 |
"outputId": "d280a1af-95db-4872-8294-0c804c3ef7b0" |
|
|
632 |
}, |
|
|
633 |
"outputs": [ |
|
|
634 |
{ |
|
|
635 |
"name": "stderr", |
|
|
636 |
"output_type": "stream", |
|
|
637 |
"text": [ |
|
|
638 |
"Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n" |
|
|
639 |
] |
|
|
640 |
}, |
|
|
641 |
{ |
|
|
642 |
"name": "stdout", |
|
|
643 |
"output_type": "stream", |
|
|
644 |
"text": [ |
|
|
645 |
" Have had one prior <Procedure>platinum-based chemotherapy regimen</Procedure> for the treatment of <Condition>primary disease</Condition>.\n", |
|
|
646 |
"\n", |
|
|
647 |
"\n", |
|
|
648 |
"\n", |
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|
649 |
"\n", |
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650 |
"\n", |
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651 |
"\n", |
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652 |
"\n", |
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653 |
"\n", |
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654 |
"\n", |
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655 |
"\n", |
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|
656 |
"\n", |
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657 |
"\n", |
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658 |
"\n", |
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"\n", |
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660 |
"\n", |
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661 |
"\n", |
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662 |
"\n", |
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663 |
"\n", |
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|
664 |
"\n", |
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665 |
"\n", |
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666 |
"\n", |
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667 |
"\n", |
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668 |
"\n", |
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|
669 |
"\n", |
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670 |
"\n", |
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671 |
"\n", |
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672 |
"\n", |
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673 |
"\n", |
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674 |
"\n", |
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675 |
"\n", |
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676 |
"\n", |
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677 |
"\n", |
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678 |
"\n", |
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679 |
"\n", |
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680 |
"\n", |
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681 |
"\n", |
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"\n", |
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683 |
"\n", |
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684 |
"\n", |
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685 |
"\n", |
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686 |
"\n", |
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687 |
"\n", |
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688 |
"\n", |
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689 |
"\n", |
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690 |
"\n", |
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691 |
"\n", |
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692 |
"\n", |
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693 |
"\n", |
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694 |
"\n", |
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695 |
"\n", |
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696 |
"\n", |
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"\n", |
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"\n", |
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"\n", |
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700 |
"\n", |
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701 |
"\n", |
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702 |
"\n", |
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703 |
"\n", |
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704 |
"\n", |
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705 |
"\n", |
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706 |
"\n", |
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707 |
"\n", |
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708 |
"\n", |
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709 |
"\n", |
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710 |
"\n", |
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711 |
"\n", |
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712 |
"\n", |
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713 |
"\n", |
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714 |
"\n", |
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715 |
"\n", |
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716 |
"\n", |
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717 |
"\n", |
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718 |
"\n", |
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719 |
"\n", |
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|
720 |
"\n", |
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|
721 |
"\n", |
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722 |
"\n", |
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|
723 |
"\n", |
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|
724 |
"\n", |
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|
725 |
"\n", |
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726 |
"\n", |
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|
727 |
"\n", |
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|
728 |
"\n", |
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729 |
"\n", |
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|
730 |
"\n", |
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|
731 |
"\n", |
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|
732 |
"\n", |
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|
733 |
"\n", |
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|
734 |
"\n", |
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|
735 |
"\n", |
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|
736 |
"\n", |
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|
737 |
"\n", |
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|
738 |
"\n", |
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|
739 |
"\n", |
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|
740 |
"\n", |
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|
741 |
"\n", |
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|
742 |
"\n", |
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|
743 |
"\n", |
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744 |
"\n", |
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745 |
"\n", |
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|
746 |
"\n", |
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|
747 |
"\n", |
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|
748 |
"\n", |
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|
749 |
"\n", |
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750 |
"\n", |
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751 |
"\n", |
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752 |
"\n", |
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753 |
"\n", |
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754 |
"\n", |
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755 |
"\n", |
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756 |
"\n", |
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|
757 |
"\n", |
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758 |
"\n", |
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759 |
"\n", |
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760 |
"\n", |
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761 |
"\n", |
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762 |
"\n", |
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763 |
"\n", |
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|
764 |
"\n", |
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765 |
"\n", |
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|
766 |
"\n", |
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|
767 |
"\n", |
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|
768 |
"\n", |
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|
769 |
"\n", |
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770 |
"\n", |
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771 |
"\n", |
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772 |
"\n", |
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|
773 |
"\n", |
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774 |
"\n", |
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775 |
"\n", |
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776 |
"\n", |
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777 |
"\n", |
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778 |
"\n", |
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779 |
"\n", |
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780 |
"\n", |
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781 |
"\n", |
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782 |
"\n", |
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783 |
"\n", |
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784 |
"\n", |
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|
785 |
"\n", |
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|
786 |
"\n", |
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|
787 |
"\n", |
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|
788 |
"\n", |
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|
789 |
"\n", |
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|
790 |
"\n", |
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791 |
"\n", |
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|
792 |
"\n", |
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793 |
"\n", |
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794 |
"\n", |
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|
795 |
"\n", |
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796 |
"\n", |
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|
797 |
"\n", |
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798 |
"\n", |
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|
799 |
"\n", |
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|
800 |
"\n", |
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|
801 |
"\n", |
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|
802 |
"\n", |
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|
803 |
"\n", |
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|
804 |
"\n", |
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|
805 |
"\n", |
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|
806 |
"\n", |
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807 |
"\n", |
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|
808 |
"\n", |
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|
809 |
"\n", |
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|
810 |
"\n", |
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|
811 |
"\n", |
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|
812 |
"\n", |
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|
813 |
"\n", |
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|
814 |
"\n", |
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|
815 |
"\n", |
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|
816 |
"\n", |
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|
817 |
"\n", |
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|
818 |
"\n", |
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|
819 |
"\n", |
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|
820 |
"\n", |
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|
821 |
"\n", |
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|
822 |
"\n", |
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|
823 |
"\n", |
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|
824 |
"\n", |
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|
825 |
"\n", |
|
|
826 |
"\n", |
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|
827 |
"\n", |
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|
828 |
"\n", |
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|
829 |
"\n", |
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|
830 |
"\n", |
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|
831 |
"\n", |
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|
832 |
"\n", |
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|
833 |
"\n", |
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|
834 |
"\n", |
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|
835 |
"\n", |
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|
836 |
"\n", |
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|
837 |
"\n", |
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|
838 |
"\n", |
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|
839 |
"\n", |
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|
840 |
"\n", |
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|
841 |
"\n", |
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|
842 |
"\n", |
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|
843 |
"\n", |
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|
844 |
"\n", |
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845 |
"\n", |
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|
846 |
"\n", |
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|
847 |
"\n", |
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|
848 |
"\n", |
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|
849 |
"\n", |
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|
850 |
"\n", |
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|
851 |
"\n", |
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852 |
"\n", |
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|
853 |
"\n", |
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|
854 |
"\n", |
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|
855 |
"\n", |
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|
856 |
"\n", |
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|
857 |
"\n", |
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|
858 |
"\n", |
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|
859 |
"\n", |
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|
860 |
"\n", |
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|
861 |
"\n", |
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|
862 |
"\n", |
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|
863 |
"\n", |
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|
864 |
"\n", |
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|
865 |
"\n", |
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|
866 |
"\n", |
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|
867 |
"\n", |
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|
868 |
"\n", |
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|
869 |
"\n", |
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|
870 |
"\n", |
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|
871 |
"\n", |
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|
872 |
"\n", |
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|
873 |
"\n", |
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874 |
"\n", |
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|
875 |
"\n", |
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|
876 |
"\n", |
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877 |
"\n", |
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|
878 |
"\n", |
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|
879 |
"\n", |
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|
880 |
"\n", |
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|
881 |
"\n", |
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|
882 |
"\n", |
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|
883 |
"\n", |
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|
884 |
"\n", |
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|
885 |
"\n", |
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|
886 |
"\n", |
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|
887 |
"\n", |
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|
888 |
"\n", |
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|
889 |
"\n", |
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|
890 |
"\n", |
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891 |
"\n", |
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|
892 |
"\n", |
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|
893 |
"\n", |
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|
894 |
"\n", |
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|
895 |
"\n", |
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|
896 |
"\n", |
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|
897 |
"\n", |
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|
898 |
"\n", |
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|
899 |
"\n", |
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|
900 |
"\n", |
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|
901 |
"\n", |
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|
902 |
"\n", |
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|
903 |
"\n", |
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|
904 |
"\n", |
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|
905 |
"\n", |
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|
906 |
"\n", |
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|
907 |
"\n", |
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|
908 |
"\n", |
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|
909 |
"\n", |
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|
910 |
"\n", |
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|
911 |
"\n", |
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|
912 |
"\n", |
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|
913 |
"\n", |
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|
914 |
"\n", |
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|
915 |
"\n", |
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|
916 |
"\n", |
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|
917 |
"\n", |
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|
918 |
"\n", |
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919 |
"\n", |
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|
920 |
"\n", |
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|
921 |
"\n", |
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922 |
"\n", |
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|
923 |
"\n", |
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924 |
"\n", |
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|
925 |
"\n", |
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|
926 |
"\n", |
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|
927 |
"\n", |
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|
928 |
"\n", |
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|
929 |
"\n", |
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|
930 |
"\n", |
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|
931 |
"\n", |
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|
932 |
"\n", |
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|
933 |
"\n", |
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|
934 |
"\n", |
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|
935 |
"\n", |
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|
936 |
"\n", |
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|
937 |
"\n", |
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|
938 |
"\n", |
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|
939 |
"\n", |
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|
940 |
"\n", |
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|
941 |
"\n", |
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942 |
"\n", |
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943 |
"\n", |
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944 |
"\n", |
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|
945 |
"\n", |
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946 |
"\n", |
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947 |
"\n", |
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|
948 |
"\n", |
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949 |
"\n", |
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950 |
"\n", |
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951 |
"\n", |
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|
952 |
"\n", |
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953 |
"\n", |
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954 |
"\n", |
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955 |
"\n", |
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956 |
"\n", |
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957 |
"\n", |
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958 |
"\n", |
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959 |
"\n", |
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960 |
"\n", |
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|
961 |
"\n", |
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|
962 |
"\n", |
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963 |
"\n", |
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|
964 |
"\n", |
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965 |
"\n", |
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|
966 |
"\n", |
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|
967 |
"\n", |
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|
968 |
"\n", |
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|
969 |
"\n", |
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|
970 |
"\n", |
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|
971 |
"\n", |
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972 |
"\n", |
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973 |
"\n", |
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974 |
"\n", |
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975 |
"\n", |
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976 |
"\n", |
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|
977 |
"\n", |
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|
978 |
"\n", |
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|
979 |
"\n", |
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|
980 |
"\n", |
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|
981 |
"\n", |
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|
982 |
"\n", |
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983 |
"\n", |
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|
984 |
"\n", |
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985 |
"\n", |
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986 |
"\n", |
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987 |
"\n", |
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|
988 |
"\n", |
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|
989 |
"\n", |
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990 |
"\n", |
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991 |
"\n", |
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|
992 |
"\n", |
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993 |
"\n", |
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994 |
"\n", |
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|
995 |
"\n", |
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|
996 |
"\n", |
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|
997 |
"\n", |
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|
998 |
"\n", |
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|
999 |
"\n", |
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|
1000 |
"\n", |
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|
1001 |
"\n", |
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|
1002 |
"\n", |
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|
1003 |
"\n", |
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|
1004 |
"\n", |
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|
1005 |
"\n", |
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|
1006 |
"\n", |
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|
1007 |
"\n", |
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1008 |
"\n", |
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|
1009 |
"\n", |
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|
1010 |
"\n", |
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|
1011 |
"\n", |
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|
1012 |
"\n", |
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|
1013 |
"\n", |
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1014 |
"\n", |
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|
1015 |
"\n", |
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|
1016 |
"\n", |
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|
1017 |
"\n", |
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|
1018 |
"\n", |
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|
1019 |
"\n", |
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|
1020 |
"\n", |
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1021 |
"\n", |
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|
1022 |
"\n", |
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|
1023 |
"\n", |
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|
1024 |
"\n", |
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|
1025 |
"\n", |
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|
1026 |
"\n", |
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|
1027 |
"\n", |
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|
1028 |
"\n", |
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|
1029 |
"\n", |
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|
1030 |
"\n", |
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|
1031 |
"\n", |
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|
1032 |
"\n", |
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|
1033 |
"\n", |
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|
1034 |
"\n", |
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|
1035 |
"\n", |
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|
1036 |
"\n", |
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|
1037 |
"\n", |
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|
1038 |
"\n", |
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|
1039 |
"\n", |
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|
1040 |
"\n", |
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1041 |
"\n", |
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|
1042 |
"\n", |
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|
1043 |
"\n", |
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|
1044 |
"\n", |
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|
1045 |
"\n", |
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1046 |
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1047 |
"\n", |
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|
1048 |
"\n", |
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1049 |
"\n", |
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|
1050 |
"\n", |
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|
1051 |
"\n", |
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|
1052 |
"\n", |
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|
1053 |
"\n", |
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|
1054 |
"\n", |
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|
1055 |
"\n", |
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|
1056 |
"\n", |
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|
1057 |
"\n", |
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|
1058 |
"\n", |
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|
1059 |
"\n", |
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|
1060 |
"\n", |
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1061 |
"\n", |
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1062 |
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1063 |
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|
1064 |
"\n", |
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1065 |
"\n", |
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1066 |
"\n", |
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1067 |
"\n", |
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1068 |
"\n", |
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1069 |
"\n", |
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|
1070 |
"\n", |
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1071 |
"\n", |
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1072 |
"\n", |
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1073 |
"\n", |
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1074 |
"\n", |
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1075 |
"\n", |
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1076 |
"\n", |
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"\n", |
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1078 |
"\n", |
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1079 |
"\n", |
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1080 |
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1081 |
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1083 |
"\n", |
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1085 |
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1086 |
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1088 |
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1089 |
"\n", |
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1090 |
"\n", |
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1093 |
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1095 |
"\n", |
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1096 |
"\n", |
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1097 |
"\n", |
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1098 |
"\n", |
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1099 |
"\n", |
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|
1100 |
"\n", |
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1101 |
"\n", |
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|
1102 |
"\n", |
|
|
1103 |
"\n", |
|
|
1104 |
"\n", |
|
|
1105 |
"\n", |
|
|
1106 |
"\n", |
|
|
1107 |
"\n", |
|
|
1108 |
"\n", |
|
|
1109 |
"\n", |
|
|
1110 |
"\n", |
|
|
1111 |
"\n", |
|
|
1112 |
"\n", |
|
|
1113 |
"\n" |
|
|
1114 |
] |
|
|
1115 |
} |
|
|
1116 |
], |
|
|
1117 |
"source": [ |
|
|
1118 |
"print(pipe(prompt_new, max_new_tokens = 500, return_full_text = False, handle_long_generation = \"hole\")[0]['generated_text'])" |
|
|
1119 |
] |
|
|
1120 |
}, |
|
|
1121 |
{ |
|
|
1122 |
"cell_type": "code", |
|
|
1123 |
"execution_count": 29, |
|
|
1124 |
"metadata": { |
|
|
1125 |
"id": "WCiUK4iEWroZ" |
|
|
1126 |
}, |
|
|
1127 |
"outputs": [], |
|
|
1128 |
"source": [ |
|
|
1129 |
"# Examples with entities not in the examples provided to the model:\n", |
|
|
1130 |
"prompt_new = '''I am working on a named entity recognition problem, in the context of clinical\n", |
|
|
1131 |
"trials eligibility criteria. I will show you the list of entities:\n", |
|
|
1132 |
"- Condition\n", |
|
|
1133 |
"- Value\n", |
|
|
1134 |
"- Drug\n", |
|
|
1135 |
"- Procedure\n", |
|
|
1136 |
"- Measurement\n", |
|
|
1137 |
"- Temporal\n", |
|
|
1138 |
"- Observation\n", |
|
|
1139 |
"- Person\n", |
|
|
1140 |
"- Mood\n", |
|
|
1141 |
"- Device\n", |
|
|
1142 |
"\n", |
|
|
1143 |
"Your task consists in annotate the named entities in a given sentence in the format I will explain you.\n", |
|
|
1144 |
"I will explain you with some examples:\n", |
|
|
1145 |
"\n", |
|
|
1146 |
"Example 1:\n", |
|
|
1147 |
"Input: Patients who have received prior chemotherapy for unresectable disease.\n", |
|
|
1148 |
"Output: Patients who have received prior <Procedure>chemotherapy</Procedure> for <Condition>unresectable disease</Condition>.\n", |
|
|
1149 |
"\n", |
|
|
1150 |
"Example 2:\n", |
|
|
1151 |
"Input: Patients with any other severe concurrent disease, which in the judgment of the investigator, would make the patient inappropriate for entry into this study.\n", |
|
|
1152 |
"Ouput: Patients with any other severe <Condition>concurrent disease</Condition>, which in the judgment of the investigator, would make the patient <Mood>inappropriate for <Observation>entry into this study</Observation>.\n", |
|
|
1153 |
"\n", |
|
|
1154 |
"As you can see, in each example, the extracted entities are enclosed using the sintax: <ENT>text of the entity</ENT>.\n", |
|
|
1155 |
"\n", |
|
|
1156 |
"Please now annotate as explained before the following sentence:\n", |
|
|
1157 |
"\n", |
|
|
1158 |
"Input: Must have had a treatment-free interval of greater than 6 months following response to platinum.\n", |
|
|
1159 |
"Output:'''" |
|
|
1160 |
] |
|
|
1161 |
}, |
|
|
1162 |
{ |
|
|
1163 |
"cell_type": "code", |
|
|
1164 |
"execution_count": 30, |
|
|
1165 |
"metadata": { |
|
|
1166 |
"colab": { |
|
|
1167 |
"base_uri": "https://localhost:8080/" |
|
|
1168 |
}, |
|
|
1169 |
"id": "nGOpCTwbXEMo", |
|
|
1170 |
"outputId": "de90319a-1347-4203-84aa-65db267a168e" |
|
|
1171 |
}, |
|
|
1172 |
"outputs": [ |
|
|
1173 |
{ |
|
|
1174 |
"name": "stderr", |
|
|
1175 |
"output_type": "stream", |
|
|
1176 |
"text": [ |
|
|
1177 |
"Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n" |
|
|
1178 |
] |
|
|
1179 |
}, |
|
|
1180 |
{ |
|
|
1181 |
"name": "stdout", |
|
|
1182 |
"output_type": "stream", |
|
|
1183 |
"text": [ |
|
|
1184 |
" Must have had a treatment-free interval of greater than <Measurement>6 months</Measurement> following response to <Drug>platinum</Drug>.\n", |
|
|
1185 |
"\n", |
|
|
1186 |
"\n", |
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1187 |
"\n", |
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1188 |
"\n", |
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1189 |
"\n", |
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1190 |
"\n", |
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1191 |
"\n", |
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1199 |
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1231 |
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1234 |
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1500 |
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|
1558 |
"\n", |
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1559 |
"\n", |
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1560 |
"\n", |
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1561 |
"\n", |
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1562 |
"\n", |
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1563 |
"\n", |
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1564 |
"\n", |
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1565 |
"\n", |
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1566 |
"\n", |
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1567 |
"\n", |
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1568 |
"\n", |
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1569 |
"\n", |
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1570 |
"\n", |
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1571 |
"\n", |
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1572 |
"\n", |
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1573 |
"\n", |
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1574 |
"\n", |
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1575 |
"\n", |
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1576 |
"\n", |
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1577 |
"\n", |
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1578 |
"\n", |
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1579 |
"\n", |
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1580 |
"\n", |
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1581 |
"\n", |
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1582 |
"\n", |
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1583 |
"\n", |
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1584 |
"\n", |
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1585 |
"\n", |
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1586 |
"\n", |
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1587 |
"\n", |
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1588 |
"\n", |
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1589 |
"\n", |
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1590 |
"\n", |
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1591 |
"\n", |
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1592 |
"\n", |
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1593 |
"\n", |
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1594 |
"\n", |
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1595 |
"\n", |
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1596 |
"\n", |
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1597 |
"\n", |
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1598 |
"\n", |
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1599 |
"\n", |
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1600 |
"\n", |
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1601 |
"\n", |
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1602 |
"\n", |
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1603 |
"\n", |
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1604 |
"\n", |
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1605 |
"\n", |
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1606 |
"\n", |
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1607 |
"\n", |
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1608 |
"\n", |
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1609 |
"\n", |
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1610 |
"\n", |
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1611 |
"\n", |
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1612 |
"\n", |
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1613 |
"\n", |
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1614 |
"\n", |
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1615 |
"\n", |
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1616 |
"\n", |
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1617 |
"\n", |
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1618 |
"\n", |
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1619 |
"\n", |
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1620 |
"\n", |
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1621 |
"\n", |
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1622 |
"\n", |
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1623 |
"\n", |
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1624 |
"\n", |
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1625 |
"\n", |
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1626 |
"\n", |
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1627 |
"\n", |
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1628 |
"\n", |
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1629 |
"\n", |
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1630 |
"\n", |
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1631 |
"\n", |
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1632 |
"\n", |
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1633 |
"\n", |
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1634 |
"\n", |
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1635 |
"\n", |
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1636 |
"\n", |
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1637 |
"\n", |
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1638 |
"\n", |
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|
1639 |
"\n", |
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|
1640 |
"\n", |
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|
1641 |
"\n", |
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|
1642 |
"\n", |
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|
1643 |
"\n", |
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|
1644 |
"\n", |
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1645 |
"\n", |
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1646 |
"\n", |
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|
1647 |
"\n", |
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1648 |
"\n", |
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|
1649 |
"\n", |
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|
1650 |
"\n" |
|
|
1651 |
] |
|
|
1652 |
} |
|
|
1653 |
], |
|
|
1654 |
"source": [ |
|
|
1655 |
"print(pipe(prompt_new, max_new_tokens = 500, return_full_text = False, handle_long_generation = \"hole\")[0]['generated_text'])" |
|
|
1656 |
] |
|
|
1657 |
}, |
|
|
1658 |
{ |
|
|
1659 |
"cell_type": "code", |
|
|
1660 |
"execution_count": 35, |
|
|
1661 |
"metadata": { |
|
|
1662 |
"id": "nZmBaRKNZ_iJ" |
|
|
1663 |
}, |
|
|
1664 |
"outputs": [], |
|
|
1665 |
"source": [ |
|
|
1666 |
"# Examples with entities not in the examples provided to the model:\n", |
|
|
1667 |
"prompt_new = '''I am working on a named entity recognition problem, in the context of clinical\n", |
|
|
1668 |
"trials eligibility criteria. I will show you the list of entities:\n", |
|
|
1669 |
"- Condition\n", |
|
|
1670 |
"- Value\n", |
|
|
1671 |
"- Drug\n", |
|
|
1672 |
"- Procedure\n", |
|
|
1673 |
"- Measurement\n", |
|
|
1674 |
"- Temporal\n", |
|
|
1675 |
"- Observation\n", |
|
|
1676 |
"- Person\n", |
|
|
1677 |
"- Mood\n", |
|
|
1678 |
"- Device\n", |
|
|
1679 |
"\n", |
|
|
1680 |
"Your task consists in annotate the named entities in a given sentence in the format I will explain you.\n", |
|
|
1681 |
"I will explain you with some examples:\n", |
|
|
1682 |
"\n", |
|
|
1683 |
"Example 1:\n", |
|
|
1684 |
"Input: Patients who have received prior chemotherapy for unresectable disease.\n", |
|
|
1685 |
"Output: Patients who have received prior <Procedure>chemotherapy</Procedure> for <Condition>unresectable disease</Condition>.\n", |
|
|
1686 |
"\n", |
|
|
1687 |
"Example 2:\n", |
|
|
1688 |
"Input: Patients with any other severe concurrent disease, which in the judgment of the investigator, would make the patient inappropriate for entry into this study.\n", |
|
|
1689 |
"Ouput: Patients with any other severe <Condition>concurrent disease</Condition>, which in the judgment of the investigator, would make the patient <Mood>inappropriate for <Observation>entry into this study</Observation>.\n", |
|
|
1690 |
"\n", |
|
|
1691 |
"Example 3:\n", |
|
|
1692 |
"Input: Must have had a treatment-free interval of greater than 6 months following response to platinum.\n", |
|
|
1693 |
"Ouput: Must have had <Condition>a treatment-free interval</Condition> of <Temporal>greater than 6 months following response to platinum</Temporal>.\n", |
|
|
1694 |
"\n", |
|
|
1695 |
"As you can see, in each example, the extracted entities are enclosed using the sintax: <ENT>text of the entity</ENT>. Take into account that sometimes it would be better to\n", |
|
|
1696 |
"keep the more general entity over specific ones.\n", |
|
|
1697 |
"\n", |
|
|
1698 |
"Please now annotate as explained before the following sentence:\n", |
|
|
1699 |
"\n", |
|
|
1700 |
"Input: At least 4 weeks since last surgery or radiation therapy.\n", |
|
|
1701 |
"Output:'''" |
|
|
1702 |
] |
|
|
1703 |
}, |
|
|
1704 |
{ |
|
|
1705 |
"cell_type": "code", |
|
|
1706 |
"execution_count": 36, |
|
|
1707 |
"metadata": { |
|
|
1708 |
"colab": { |
|
|
1709 |
"base_uri": "https://localhost:8080/" |
|
|
1710 |
}, |
|
|
1711 |
"id": "Mkk90J_OaMBK", |
|
|
1712 |
"outputId": "57dc6915-6bf4-45ae-e3a1-0e410181795e" |
|
|
1713 |
}, |
|
|
1714 |
"outputs": [ |
|
|
1715 |
{ |
|
|
1716 |
"name": "stderr", |
|
|
1717 |
"output_type": "stream", |
|
|
1718 |
"text": [ |
|
|
1719 |
"/usr/local/lib/python3.10/dist-packages/transformers/pipelines/base.py:1157: UserWarning: You seem to be using the pipelines sequentially on GPU. In order to maximize efficiency please use a dataset\n", |
|
|
1720 |
" warnings.warn(\n", |
|
|
1721 |
"Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n" |
|
|
1722 |
] |
|
|
1723 |
}, |
|
|
1724 |
{ |
|
|
1725 |
"name": "stdout", |
|
|
1726 |
"output_type": "stream", |
|
|
1727 |
"text": [ |
|
|
1728 |
" At least 4 weeks since <Procedure>last surgery</Procedure> or <Procedure>radiation therapy</Procedure>.\n", |
|
|
1729 |
"\n", |
|
|
1730 |
"\n", |
|
|
1731 |
"\n", |
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|
1732 |
"\n", |
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1733 |
"\n", |
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1734 |
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1735 |
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1736 |
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1738 |
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"\n", |
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"\n", |
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"\n", |
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2009 |
"\n", |
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} |
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