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b/lit_gpt/config.py |
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import json |
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from copy import deepcopy |
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from dataclasses import dataclass, field |
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from pathlib import Path |
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from typing import Any, Literal, Optional, Type, Union |
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import torch |
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from typing_extensions import Self |
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import lit_gpt.model |
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from lit_gpt.utils import find_multiple |
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@dataclass |
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class Config: |
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name: str = "" |
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hf_config: dict = field(default_factory=dict) |
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block_size: int = 4096 |
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vocab_size: int = 50254 |
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padding_multiple: int = 512 |
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padded_vocab_size: Optional[int] = None |
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n_layer: int = 16 |
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n_head: int = 32 |
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n_embd: int = 4096 |
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rotary_percentage: float = 0.25 |
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parallel_residual: bool = True |
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bias: bool = True |
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lm_head_bias: bool = False |
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# to use multi-head attention (MHA), set this to `n_head` (default) |
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# to use multi-query attention (MQA), set this to 1 |
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# to use grouped-query attention (GQA), set this to a value in between |
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# Example with `n_head=4` |
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# ┌───┐┌───┐┌───┐┌───┐ ┌───┐ ┌───┐ ┌───┐ |
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# │ v ││ v ││ v ││ v │ │ v │ │ v │ │ v │ |
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# └───┘└───┘└───┘└───┘ └───┘ └───┘ └───┘ |
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# │ │ │ │ │ │ │ |
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# ┌───┐┌───┐┌───┐┌───┐ ┌───┐ ┌───┐ ┌───┐ |
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# │ k ││ k ││ k ││ k │ │ k │ │ k │ │ k │ |
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# └───┘└───┘└───┘└───┘ └───┘ └───┘ └───┘ |
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# │ │ │ │ ┌──┴──┐ ┌──┴──┐ ┌────┬──┴─┬────┐ |
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# ┌───┐┌───┐┌───┐┌───┐ ┌───┐┌───┐┌───┐┌───┐ ┌───┐┌───┐┌───┐┌───┐ |
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# │ q ││ q ││ q ││ q │ │ q ││ q ││ q ││ q │ │ q ││ q ││ q ││ q │ |
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# └───┘└───┘└───┘└───┘ └───┘└───┘└───┘└───┘ └───┘└───┘└───┘└───┘ |
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# ◀──────────────────▶ ◀──────────────────▶ ◀──────────────────▶ |
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# MHA GQA MQA |
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# n_query_groups=4 n_query_groups=2 n_query_groups=1 |
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# |
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# credit https://arxiv.org/pdf/2305.13245.pdf |
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n_query_groups: Optional[int] = None |
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shared_attention_norm: bool = False |
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_norm_class: Literal["LayerNorm", "RMSNorm"] = "LayerNorm" |
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norm_eps: float = 1e-5 |
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_mlp_class: Literal["GptNeoxMLP", "LLaMAMLP"] = "GptNeoxMLP" |
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gelu_approximate: str = "none" |
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intermediate_size: Optional[int] = None |
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rope_condense_ratio: int = 1 |
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rope_base: int = 10000 |
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def __post_init__(self): |
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if not self.name: |
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self.name = self.hf_config.get("name", self.name) |
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assert self.n_embd % self.n_head == 0 |
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self.head_size = self.n_embd // self.n_head |
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# vocab size should be a power of 2 to be optimal on hardware. compute the closest value |
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if self.padded_vocab_size is None: |
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self.padded_vocab_size = find_multiple(self.vocab_size, self.padding_multiple) |
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else: |
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# vocab size shouldn't be larger than padded vocab size |
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self.vocab_size = min(self.vocab_size, self.padded_vocab_size) |
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# compute the number of query groups |
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if self.n_query_groups is not None: |
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assert self.n_head % self.n_query_groups == 0 |
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else: |
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self.n_query_groups = self.n_head |
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# compute the intermediate size for MLP if not set |
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if self.intermediate_size is None: |
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if self._mlp_class == "LLaMAMLP": |
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raise ValueError("The config needs to set the `intermediate_size`") |
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self.intermediate_size = 4 * self.n_embd |
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self.rope_n_elem = int(self.rotary_percentage * self.head_size) |
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@classmethod |
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def from_name(cls, name: str, **kwargs: Any) -> Self: |
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if name not in name_to_config: |
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# search through all `config['hf_config']['name']` |
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try: |
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conf_dict = next(config for config in configs if name == config["hf_config"]["name"]) |
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except StopIteration: |
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raise ValueError(f"{name!r} is not a supported config name") |
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else: |
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conf_dict = name_to_config[name] |
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conf_dict = conf_dict.copy() |
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if "condense_ratio" in kwargs: # legacy name |
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kwargs["rope_condense_ratio"] = kwargs.pop("condense_ratio") |
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conf_dict.update(kwargs) |
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return cls(**conf_dict) |
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@classmethod |
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def from_json(cls, path: Union[str, Path], **kwargs: Any) -> Self: |
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with open(path, encoding="utf-8") as fp: |
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json_kwargs = json.load(fp) |
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if "condense_ratio" in json_kwargs: # legacy name |
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json_kwargs["rope_condense_ratio"] = json_kwargs.pop("condense_ratio") |
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if "condense_ratio" in kwargs: # legacy name |
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kwargs["rope_condense_ratio"] = kwargs.pop("condense_ratio") |
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if "org" in json_kwargs: # legacy name |
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json_kwargs["hf_config"] = {"name": json_kwargs["name"], "org": json_kwargs.pop("org")} |
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if "org" in kwargs: # legacy name |
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kwargs["hf_config"] = {"name": kwargs.get("name", json_kwargs["name"]), "org": kwargs.pop("org")} |
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json_kwargs.update(kwargs) |
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return cls(**json_kwargs) |
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@classmethod |
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def from_checkpoint(cls, path: Path, **kwargs: Any) -> Self: |
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"""Automatically load `lit_config.json` and if it doesn't exist - a matching config from `lit_gpt/config.py`.""" |
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if (config_path := path / "lit_config.json").is_file(): |
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return cls.from_json(config_path, **kwargs) |
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if (model_name := path.name) in name_to_config: |
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return cls.from_name(model_name, **kwargs) |
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raise FileNotFoundError(f"For {str(path)!r} neither 'lit_config.json' nor matching config exists.") |
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@property |
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def mlp_class(self) -> Type: |
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# `self._mlp_class` cannot be the type to keep the config json serializable |
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return getattr(lit_gpt.model, self._mlp_class) |
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@property |
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def norm_class(self) -> Type: |
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# `self._norm_class` cannot be the type to keep the config json serializable |
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if self._norm_class == "RMSNorm": |
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from lit_gpt.rmsnorm import RMSNorm |
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return RMSNorm |
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return getattr(torch.nn, self._norm_class) |
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######################## |
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# Stability AI StableLM |
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######################## |
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configs = [ |
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# https://huggingface.co/stabilityai/stablelm-base-alpha-3b/blob/main/config.json |
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dict(name="stablelm-base-alpha-3b", hf_config=dict(org="stabilityai", name="stablelm-base-alpha-3b")), |
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# https://huggingface.co/stabilityai/stablelm-base-alpha-7b/blob/main/config.json |
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dict( |
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name="stablelm-base-alpha-7b", |
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hf_config=dict(org="stabilityai", name="stablelm-base-alpha-7b"), |
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n_head=48, |
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n_embd=6144, |
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padding_multiple=256, |
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), |
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# https://huggingface.co/stabilityai/stablelm-tuned-alpha-3b/blob/main/config.json |
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dict(name="stablelm-tuned-alpha-3b", hf_config=dict(org="stabilityai", name="stablelm-tuned-alpha-3b"), n_head=32), |
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# https://huggingface.co/stabilityai/stablelm-tuned-alpha-7b/blob/main/config.json |
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dict( |
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name="stablelm-tuned-alpha-7b", |
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hf_config=dict(org="stabilityai", name="stablelm-tuned-alpha-7b"), |
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n_head=48, |
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n_embd=6144, |
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padding_multiple=256, |
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), |
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] |
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#################### |
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# EleutherAI Pythia |
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#################### |
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pythia = [ |
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# https://huggingface.co/EleutherAI/pythia-14m/blob/main/config.json |
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dict( |
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name="pythia-14m", |
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hf_config=dict(org="EleutherAI", name="pythia-14m"), |
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block_size=512, |
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n_layer=6, |
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n_embd=128, |
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n_head=4, |
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padding_multiple=128, |
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), |
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# https://huggingface.co/EleutherAI/pythia-31m/blob/main/config.json |
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dict( |
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name="pythia-31m", |
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hf_config=dict(org="EleutherAI", name="pythia-31m"), |
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block_size=1024, |
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n_layer=6, |
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n_embd=256, |
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n_head=8, |
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padding_multiple=128, |
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), |
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# https://huggingface.co/EleutherAI/pythia-70m/blob/main/config.json |
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dict( |
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name="pythia-70m", |
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hf_config=dict(org="EleutherAI", name="pythia-70m"), |
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block_size=2048, |
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n_layer=6, |
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n_embd=512, |
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n_head=8, |
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padding_multiple=128, |
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), |
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# https://huggingface.co/EleutherAI/pythia-160m/blob/main/config.json |
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dict( |
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name="pythia-160m", |
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hf_config=dict(org="EleutherAI", name="pythia-160m"), |
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block_size=2048, |
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n_layer=12, |
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n_embd=768, |
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n_head=12, |
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padding_multiple=128, |
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), |
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# https://huggingface.co/EleutherAI/pythia-410m/blob/main/config.json |
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dict( |
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name="pythia-410m", |
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hf_config=dict(org="EleutherAI", name="pythia-410m"), |
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block_size=2048, |
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n_layer=24, |
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n_embd=1024, |
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n_head=16, |
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padding_multiple=128, |
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), |
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# https://huggingface.co/EleutherAI/pythia-1b/blob/main/config.json |
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dict( |
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name="pythia-1b", |
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hf_config=dict(org="EleutherAI", name="pythia-1b"), |
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block_size=2048, |
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n_embd=2048, |
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n_head=8, |
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padding_multiple=128, |
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), |
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# https://huggingface.co/EleutherAI/pythia-1.4b/blob/main/config.json |
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dict( |
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name="pythia-1.4b", |
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hf_config=dict(org="EleutherAI", name="pythia-1.4b"), |
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block_size=2048, |
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n_layer=24, |
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n_embd=2048, |
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n_head=16, |
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padding_multiple=128, |
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), |
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# https://huggingface.co/EleutherAI/pythia-2.8b/blob/main/config.json |
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dict( |
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name="pythia-2.8b", |
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hf_config=dict(org="EleutherAI", name="pythia-2.8b"), |
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block_size=2048, |
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n_layer=32, |
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n_embd=2560, |
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padding_multiple=128, |
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), |
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# https://huggingface.co/EleutherAI/pythia-6.9b/blob/main/config.json |
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dict( |
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name="pythia-6.9b", |
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hf_config=dict(org="EleutherAI", name="pythia-6.9b"), |
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block_size=2048, |
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n_layer=32, |
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padding_multiple=256, |
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), |
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# https://huggingface.co/EleutherAI/pythia-12b/blob/main/config.json |
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dict( |
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name="pythia-12b", |
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hf_config=dict(org="EleutherAI", name="pythia-12b"), |
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block_size=2048, |
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n_layer=36, |
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n_embd=5120, |
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n_head=40, |
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), |
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] |
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configs.extend(pythia) |
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for c in pythia: |
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# "pythia-14m" and "pythia-31m" don't have deduped version |
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if c["name"] in ("pythia-14m", "pythia-31m"): |
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continue |
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copy = deepcopy(c) |
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copy["name"] = f"{c['name']}-deduped" |
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copy["hf_config"]["name"] = f"{c['hf_config']['name']}-deduped" |
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configs.append(copy) |
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278 |
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279 |
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#################################### |
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# togethercomputer RedPajama INCITE |
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#################################### |
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redpajama_incite = [ |
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# https://huggingface.co/togethercomputer/RedPajama-INCITE-Base-3B-v1/blob/main/config.json |
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dict( |
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name="RedPajama-INCITE-{}-3B-v1", |
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hf_config=dict(org="togethercomputer", name="RedPajama-INCITE-{}-3B-v1"), |
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block_size=2048, |
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n_layer=32, |
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n_embd=2560, |
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padding_multiple=256, |
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rotary_percentage=1.0, |
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parallel_residual=False, |
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), |
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# https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Base/blob/main/config.json |
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dict( |
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name="RedPajama-INCITE-7B-{}", |
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hf_config=dict(org="togethercomputer", name="RedPajama-INCITE-7B-{}"), |
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block_size=2048, |
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n_layer=32, |
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padding_multiple=256, |
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rotary_percentage=1.0, |
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parallel_residual=False, |
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), |
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# this redirects to the checkpoint above. kept for those who had the old weights already downloaded |
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dict( |
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name="RedPajama-INCITE-{}-7B-v0.1", |
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hf_config=dict(org="togethercomputer", name="RedPajama-INCITE-{}-7B-v0.1"), |
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block_size=2048, |
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n_layer=32, |
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padding_multiple=256, |
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rotary_percentage=1.0, |
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parallel_residual=False, |
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), |
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] |
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for c in redpajama_incite: |
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for kind in ("Base", "Chat", "Instruct"): |
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copy = deepcopy(c) |
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copy["name"] = c["name"].format(kind) |
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copy["hf_config"]["name"] = c["hf_config"]["name"].format(kind) |
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configs.append(copy) |
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322 |
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323 |
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324 |
################# |
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325 |
# TII UAE Falcon |
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326 |
################# |
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327 |
falcon = [ |
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328 |
# https://huggingface.co/tiiuae/falcon-7b/blob/main/config.json |
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329 |
dict( |
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330 |
name="falcon-7b{}", |
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331 |
hf_config=dict(org="tiiuae", name="falcon-7b{}"), |
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block_size=2048, |
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333 |
vocab_size=65024, |
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padded_vocab_size=65024, |
|
|
335 |
n_layer=32, |
|
|
336 |
n_head=71, |
|
|
337 |
n_embd=4544, |
|
|
338 |
rotary_percentage=1.0, |
|
|
339 |
n_query_groups=1, |
|
|
340 |
bias=False, |
|
|
341 |
# this is not in the config, but in the original model implementation, only for this config |
|
|
342 |
shared_attention_norm=True, |
|
|
343 |
), |
|
|
344 |
# https://huggingface.co/tiiuae/falcon-40b/blob/main/config.json |
|
|
345 |
dict( |
|
|
346 |
name="falcon-40b{}", |
|
|
347 |
hf_config=dict(org="tiiuae", name="falcon-40b{}"), |
|
|
348 |
block_size=2048, |
|
|
349 |
vocab_size=65024, |
|
|
350 |
padded_vocab_size=65024, |
|
|
351 |
n_layer=60, |
|
|
352 |
n_head=128, |
|
|
353 |
n_embd=8192, |
|
|
354 |
rotary_percentage=1.0, |
|
|
355 |
n_query_groups=8, |
|
|
356 |
bias=False, |
|
|
357 |
), |
|
|
358 |
] |
|
|
359 |
for c in falcon: |
|
|
360 |
for kind in ("", "-instruct"): |
|
|
361 |
copy = deepcopy(c) |
|
|
362 |
copy["name"] = c["name"].format(kind) |
|
|
363 |
copy["hf_config"]["name"] = c["hf_config"]["name"].format(kind) |
|
|
364 |
configs.append(copy) |
|
|
365 |
|
|
|
366 |
# https://huggingface.co/tiiuae/falcon-180b/blob/main/config.json |
|
|
367 |
falcon180b = dict( |
|
|
368 |
name="falcon-180B{}", |
|
|
369 |
hf_config=dict(org="tiiuae", name="falcon-180B{}"), |
|
|
370 |
block_size=2048, |
|
|
371 |
vocab_size=65024, |
|
|
372 |
padded_vocab_size=65024, |
|
|
373 |
n_layer=80, |
|
|
374 |
n_head=232, |
|
|
375 |
n_embd=14848, |
|
|
376 |
rotary_percentage=1.0, |
|
|
377 |
n_query_groups=8, |
|
|
378 |
bias=False, |
|
|
379 |
) |
|
|
380 |
|
|
|
381 |
for kind in ("", "-chat"): |
|
|
382 |
copy = deepcopy(falcon180b) |
|
|
383 |
copy["name"] = falcon180b["name"].format(kind) |
|
|
384 |
copy["hf_config"]["name"] = falcon180b["hf_config"]["name"].format(kind) |
|
|
385 |
configs.append(copy) |
|
|
386 |
|
|
|
387 |
|
|
|
388 |
############################# |
|
|
389 |
# OpenLM Research Open LLaMA |
|
|
390 |
############################# |
|
|
391 |
open_LLaMA = [ |
|
|
392 |
# https://huggingface.co/openlm-research/open_llama_3b/blob/main/config.json |
|
|
393 |
dict( |
|
|
394 |
name="open_llama_3b", |
|
|
395 |
hf_config=dict(org="openlm-research", name="open_llama_3b"), |
|
|
396 |
block_size=2048, |
|
|
397 |
vocab_size=32000, |
|
|
398 |
padding_multiple=64, |
|
|
399 |
n_layer=26, |
|
|
400 |
n_embd=3200, |
|
|
401 |
rotary_percentage=1.0, |
|
|
402 |
parallel_residual=False, |
|
|
403 |
bias=False, |
|
|
404 |
_norm_class="RMSNorm", |
|
|
405 |
norm_eps=1e-6, |
|
|
406 |
_mlp_class="LLaMAMLP", |
|
|
407 |
intermediate_size=8640, |
|
|
408 |
), |
|
|
409 |
# https://huggingface.co/openlm-research/open_llama_7b/blob/main/config.json |
|
|
410 |
dict( |
|
|
411 |
name="open_llama_7b", |
|
|
412 |
hf_config=dict(org="openlm-research", name="open_llama_7b"), |
|
|
413 |
block_size=2048, |
|
|
414 |
vocab_size=32000, |
|
|
415 |
padding_multiple=64, |
|
|
416 |
n_layer=32, |
|
|
417 |
rotary_percentage=1.0, |
|
|
418 |
parallel_residual=False, |
|
|
419 |
bias=False, |
|
|
420 |
_norm_class="RMSNorm", |
|
|
421 |
norm_eps=1e-6, |
|
|
422 |
_mlp_class="LLaMAMLP", |
|
|
423 |
intermediate_size=11008, |
|
|
424 |
), |
|
|
425 |
# https://huggingface.co/openlm-research/open_llama_13b/blob/main/config.json |
|
|
426 |
dict( |
|
|
427 |
name="open_llama_13b", |
|
|
428 |
hf_config=dict(org="openlm-research", name="open_llama_13b"), |
|
|
429 |
block_size=2048, |
|
|
430 |
vocab_size=32000, |
|
|
431 |
padding_multiple=64, |
|
|
432 |
n_layer=40, |
|
|
433 |
n_head=40, |
|
|
434 |
n_embd=5120, |
|
|
435 |
rotary_percentage=1.0, |
|
|
436 |
parallel_residual=False, |
|
|
437 |
bias=False, |
|
|
438 |
_norm_class="RMSNorm", |
|
|
439 |
norm_eps=1e-6, |
|
|
440 |
_mlp_class="LLaMAMLP", |
|
|
441 |
intermediate_size=13824, |
|
|
442 |
), |
|
|
443 |
] |
|
|
444 |
configs.extend(open_LLaMA) |
|
|
445 |
|
|
|
446 |
|
|
|
447 |
############### |
|
|
448 |
# LMSYS Vicuna |
|
|
449 |
############### |
|
|
450 |
vicuna = [ |
|
|
451 |
# https://huggingface.co/lmsys/vicuna-7b-v1.3/blob/main/config.json |
|
|
452 |
dict( |
|
|
453 |
name="vicuna-7b-v1.3", |
|
|
454 |
hf_config=dict(org="lmsys", name="vicuna-7b-v1.3"), |
|
|
455 |
block_size=2048, |
|
|
456 |
vocab_size=32000, |
|
|
457 |
padding_multiple=64, |
|
|
458 |
n_layer=32, |
|
|
459 |
rotary_percentage=1.0, |
|
|
460 |
parallel_residual=False, |
|
|
461 |
bias=False, |
|
|
462 |
_norm_class="RMSNorm", |
|
|
463 |
norm_eps=1e-6, |
|
|
464 |
_mlp_class="LLaMAMLP", |
|
|
465 |
intermediate_size=11008, |
|
|
466 |
), |
|
|
467 |
# https://huggingface.co/lmsys/vicuna-13b-v1.3/blob/main/config.json |
|
|
468 |
dict( |
|
|
469 |
name="vicuna-13b-v1.3", |
|
|
470 |
hf_config=dict(org="lmsys", name="vicuna-13b-v1.3"), |
|
|
471 |
block_size=2048, |
|
|
472 |
vocab_size=32000, |
|
|
473 |
padding_multiple=64, |
|
|
474 |
n_layer=40, |
|
|
475 |
n_head=40, |
|
|
476 |
n_embd=5120, |
|
|
477 |
rotary_percentage=1.0, |
|
|
478 |
parallel_residual=False, |
|
|
479 |
bias=False, |
|
|
480 |
_norm_class="RMSNorm", |
|
|
481 |
norm_eps=1e-6, |
|
|
482 |
_mlp_class="LLaMAMLP", |
|
|
483 |
intermediate_size=13824, |
|
|
484 |
), |
|
|
485 |
# https://huggingface.co/lmsys/vicuna-33b-v1.3/blob/main/config.json |
|
|
486 |
dict( |
|
|
487 |
name="vicuna-33b-v1.3", |
|
|
488 |
hf_config=dict(org="lmsys", name="vicuna-33b-v1.3"), |
|
|
489 |
block_size=2048, |
|
|
490 |
vocab_size=32000, |
|
|
491 |
padding_multiple=64, |
|
|
492 |
n_layer=60, |
|
|
493 |
n_head=52, |
|
|
494 |
n_embd=6656, |
|
|
495 |
rotary_percentage=1.0, |
|
|
496 |
parallel_residual=False, |
|
|
497 |
bias=False, |
|
|
498 |
_norm_class="RMSNorm", |
|
|
499 |
norm_eps=1e-6, |
|
|
500 |
_mlp_class="LLaMAMLP", |
|
|
501 |
intermediate_size=17920, |
|
|
502 |
), |
|
|
503 |
# https://huggingface.co/lmsys/vicuna-7b-v1.5/blob/main/config.json |
|
|
504 |
dict( |
|
|
505 |
name="vicuna-7b-v1.5", |
|
|
506 |
hf_config=dict(org="lmsys", name="vicuna-7b-v1.5"), |
|
|
507 |
vocab_size=32000, |
|
|
508 |
padding_multiple=64, |
|
|
509 |
n_layer=32, |
|
|
510 |
rotary_percentage=1.0, |
|
|
511 |
parallel_residual=False, |
|
|
512 |
bias=False, |
|
|
513 |
_norm_class="RMSNorm", |
|
|
514 |
_mlp_class="LLaMAMLP", |
|
|
515 |
intermediate_size=11008, |
|
|
516 |
), |
|
|
517 |
# https://huggingface.co/lmsys/vicuna-7b-v1.5-16k/blob/main/config.json |
|
|
518 |
dict( |
|
|
519 |
name="vicuna-7b-v1.5-16k", |
|
|
520 |
hf_config=dict(org="lmsys", name="vicuna-7b-v1.5-16k"), |
|
|
521 |
block_size=16384, |
|
|
522 |
vocab_size=32000, |
|
|
523 |
padding_multiple=64, |
|
|
524 |
n_layer=32, |
|
|
525 |
rotary_percentage=1.0, |
|
|
526 |
parallel_residual=False, |
|
|
527 |
bias=False, |
|
|
528 |
_norm_class="RMSNorm", |
|
|
529 |
_mlp_class="LLaMAMLP", |
|
|
530 |
intermediate_size=11008, |
|
|
531 |
rope_condense_ratio=4, |
|
|
532 |
), |
|
|
533 |
# https://huggingface.co/lmsys/vicuna-13b-v1.5/blob/main/config.json |
|
|
534 |
dict( |
|
|
535 |
name="vicuna-13b-v1.5", |
|
|
536 |
hf_config=dict(org="lmsys", name="vicuna-13b-v1.5"), |
|
|
537 |
vocab_size=32000, |
|
|
538 |
padding_multiple=64, |
|
|
539 |
n_layer=40, |
|
|
540 |
n_head=40, |
|
|
541 |
n_embd=5120, |
|
|
542 |
rotary_percentage=1.0, |
|
|
543 |
parallel_residual=False, |
|
|
544 |
bias=False, |
|
|
545 |
_norm_class="RMSNorm", |
|
|
546 |
_mlp_class="LLaMAMLP", |
|
|
547 |
intermediate_size=13824, |
|
|
548 |
), |
|
|
549 |
# https://huggingface.co/lmsys/vicuna-13b-v1.5-16k/blob/main/config.json |
|
|
550 |
dict( |
|
|
551 |
name="vicuna-13b-v1.5-16k", |
|
|
552 |
hf_config=dict(org="lmsys", name="vicuna-13b-v1.5-16k"), |
|
|
553 |
block_size=16384, |
|
|
554 |
vocab_size=32000, |
|
|
555 |
padding_multiple=64, |
|
|
556 |
n_layer=40, |
|
|
557 |
n_head=40, |
|
|
558 |
n_embd=5120, |
|
|
559 |
rotary_percentage=1.0, |
|
|
560 |
parallel_residual=False, |
|
|
561 |
bias=False, |
|
|
562 |
_norm_class="RMSNorm", |
|
|
563 |
_mlp_class="LLaMAMLP", |
|
|
564 |
intermediate_size=13824, |
|
|
565 |
rope_condense_ratio=4, |
|
|
566 |
), |
|
|
567 |
] |
|
|
568 |
configs.extend(vicuna) |
|
|
569 |
|
|
|
570 |
|
|
|
571 |
################# |
|
|
572 |
# LMSYS LongChat |
|
|
573 |
################# |
|
|
574 |
long_chat = [ |
|
|
575 |
# https://huggingface.co/lmsys/longchat-7b-16k/blob/main/config.json |
|
|
576 |
dict( |
|
|
577 |
name="longchat-7b-16k", |
|
|
578 |
hf_config=dict(org="lmsys", name="longchat-7b-16k"), |
|
|
579 |
block_size=16384, |
|
|
580 |
vocab_size=32000, |
|
|
581 |
padding_multiple=64, |
|
|
582 |
n_layer=32, |
|
|
583 |
rotary_percentage=1.0, |
|
|
584 |
parallel_residual=False, |
|
|
585 |
bias=False, |
|
|
586 |
_norm_class="RMSNorm", |
|
|
587 |
norm_eps=1e-6, |
|
|
588 |
_mlp_class="LLaMAMLP", |
|
|
589 |
intermediate_size=11008, |
|
|
590 |
rope_condense_ratio=8, |
|
|
591 |
), |
|
|
592 |
# https://huggingface.co/lmsys/longchat-13b-16k/blob/main/config.json |
|
|
593 |
dict( |
|
|
594 |
name="longchat-13b-16k", |
|
|
595 |
hf_config=dict(org="lmsys", name="longchat-13b-16k"), |
|
|
596 |
block_size=16384, |
|
|
597 |
vocab_size=32000, |
|
|
598 |
padding_multiple=64, |
|
|
599 |
n_layer=40, |
|
|
600 |
n_head=40, |
|
|
601 |
n_embd=5120, |
|
|
602 |
rotary_percentage=1.0, |
|
|
603 |
parallel_residual=False, |
|
|
604 |
bias=False, |
|
|
605 |
_norm_class="RMSNorm", |
|
|
606 |
norm_eps=1e-6, |
|
|
607 |
_mlp_class="LLaMAMLP", |
|
|
608 |
intermediate_size=13824, |
|
|
609 |
rope_condense_ratio=8, |
|
|
610 |
), |
|
|
611 |
] |
|
|
612 |
configs.extend(long_chat) |
|
|
613 |
|
|
|
614 |
|
|
|
615 |
###################### |
|
|
616 |
# NousResearch Hermes |
|
|
617 |
###################### |
|
|
618 |
nous_research = [ |
|
|
619 |
# https://huggingface.co/NousResearch/Nous-Hermes-llama-2-7b/blob/main/config.json |
|
|
620 |
dict( |
|
|
621 |
name="Nous-Hermes-llama-2-7b", |
|
|
622 |
hf_config=dict(org="NousResearch", name="Nous-Hermes-llama-2-7b"), |
|
|
623 |
padded_vocab_size=32000, |
|
|
624 |
n_layer=32, |
|
|
625 |
rotary_percentage=1.0, |
|
|
626 |
parallel_residual=False, |
|
|
627 |
bias=False, |
|
|
628 |
_norm_class="RMSNorm", |
|
|
629 |
norm_eps=1e-05, |
|
|
630 |
_mlp_class="LLaMAMLP", |
|
|
631 |
intermediate_size=11008, |
|
|
632 |
), |
|
|
633 |
# https://huggingface.co/NousResearch/Nous-Hermes-13B/blob/main/config.json |
|
|
634 |
dict( |
|
|
635 |
name="Nous-Hermes-13b", |
|
|
636 |
hf_config=dict(org="NousResearch", name="Nous-Hermes-13b"), |
|
|
637 |
block_size=2048, |
|
|
638 |
vocab_size=32000, |
|
|
639 |
padded_vocab_size=32001, |
|
|
640 |
n_layer=40, |
|
|
641 |
n_head=40, |
|
|
642 |
n_embd=5120, |
|
|
643 |
rotary_percentage=1.0, |
|
|
644 |
parallel_residual=False, |
|
|
645 |
bias=False, |
|
|
646 |
_norm_class="RMSNorm", |
|
|
647 |
norm_eps=1e-6, |
|
|
648 |
_mlp_class="LLaMAMLP", |
|
|
649 |
intermediate_size=13824, |
|
|
650 |
), |
|
|
651 |
# https://huggingface.co/NousResearch/Nous-Hermes-Llama2-13b |
|
|
652 |
dict( |
|
|
653 |
name="Nous-Hermes-Llama2-13b", |
|
|
654 |
hf_config=dict(org="NousResearch", name="Nous-Hermes-Llama2-13b"), |
|
|
655 |
vocab_size=32000, |
|
|
656 |
padded_vocab_size=32032, |
|
|
657 |
n_layer=40, |
|
|
658 |
n_head=40, |
|
|
659 |
n_embd=5120, |
|
|
660 |
rotary_percentage=1.0, |
|
|
661 |
parallel_residual=False, |
|
|
662 |
bias=False, |
|
|
663 |
_norm_class="RMSNorm", |
|
|
664 |
norm_eps=1e-05, |
|
|
665 |
_mlp_class="LLaMAMLP", |
|
|
666 |
intermediate_size=13824, |
|
|
667 |
), |
|
|
668 |
] |
|
|
669 |
configs.extend(nous_research) |
|
|
670 |
|
|
|
671 |
|
|
|
672 |
############### |
|
|
673 |
# Meta LLaMA 2 |
|
|
674 |
############### |
|
|
675 |
llama_2 = [ |
|
|
676 |
# https://huggingface.co/meta-llama/Llama-2-7b-hf/blob/main/config.json |
|
|
677 |
dict( |
|
|
678 |
name="Llama-2-7b{}-hf", |
|
|
679 |
hf_config=dict(org="meta-llama", name="Llama-2-7b{}-hf"), |
|
|
680 |
vocab_size=32000, |
|
|
681 |
padding_multiple=64, |
|
|
682 |
n_layer=32, |
|
|
683 |
rotary_percentage=1.0, |
|
|
684 |
parallel_residual=False, |
|
|
685 |
bias=False, |
|
|
686 |
_norm_class="RMSNorm", |
|
|
687 |
_mlp_class="LLaMAMLP", |
|
|
688 |
intermediate_size=11008, |
|
|
689 |
), |
|
|
690 |
# https://huggingface.co/meta-llama/Llama-2-13b-hf/blob/main/config.json |
|
|
691 |
dict( |
|
|
692 |
name="Llama-2-13b{}-hf", |
|
|
693 |
hf_config=dict(org="meta-llama", name="Llama-2-13b{}-hf"), |
|
|
694 |
vocab_size=32000, |
|
|
695 |
padding_multiple=64, |
|
|
696 |
n_layer=40, |
|
|
697 |
n_head=40, |
|
|
698 |
n_embd=5120, |
|
|
699 |
rotary_percentage=1.0, |
|
|
700 |
parallel_residual=False, |
|
|
701 |
bias=False, |
|
|
702 |
_norm_class="RMSNorm", |
|
|
703 |
_mlp_class="LLaMAMLP", |
|
|
704 |
intermediate_size=13824, |
|
|
705 |
), |
|
|
706 |
# https://huggingface.co/meta-llama/Llama-2-70b-hf/blob/main/config.json |
|
|
707 |
dict( |
|
|
708 |
name="Llama-2-70b{}-hf", |
|
|
709 |
hf_config=dict(org="meta-llama", name="Llama-2-70b{}-hf"), |
|
|
710 |
vocab_size=32000, |
|
|
711 |
padding_multiple=64, |
|
|
712 |
n_layer=80, |
|
|
713 |
n_head=64, |
|
|
714 |
n_embd=8192, |
|
|
715 |
n_query_groups=8, |
|
|
716 |
rotary_percentage=1.0, |
|
|
717 |
parallel_residual=False, |
|
|
718 |
bias=False, |
|
|
719 |
_norm_class="RMSNorm", |
|
|
720 |
_mlp_class="LLaMAMLP", |
|
|
721 |
intermediate_size=28672, |
|
|
722 |
), |
|
|
723 |
] |
|
|
724 |
for c in llama_2: |
|
|
725 |
for kind in ("", "-chat"): |
|
|
726 |
copy = deepcopy(c) |
|
|
727 |
copy["name"] = c["name"].format(kind) |
|
|
728 |
copy["hf_config"]["name"] = c["hf_config"]["name"].format(kind) |
|
|
729 |
configs.append(copy) |
|
|
730 |
|
|
|
731 |
|
|
|
732 |
########################## |
|
|
733 |
# Stability AI FreeWilly2 |
|
|
734 |
########################## |
|
|
735 |
freewilly_2 = [ |
|
|
736 |
# https://huggingface.co/stabilityai/FreeWilly2/blob/main/config.json |
|
|
737 |
dict( |
|
|
738 |
name="FreeWilly2", |
|
|
739 |
hf_config=dict(org="stabilityai", name="FreeWilly2"), |
|
|
740 |
vocab_size=32000, |
|
|
741 |
padding_multiple=64, |
|
|
742 |
n_layer=80, |
|
|
743 |
n_head=64, |
|
|
744 |
n_embd=8192, |
|
|
745 |
n_query_groups=8, |
|
|
746 |
rotary_percentage=1.0, |
|
|
747 |
parallel_residual=False, |
|
|
748 |
bias=False, |
|
|
749 |
_norm_class="RMSNorm", |
|
|
750 |
_mlp_class="LLaMAMLP", |
|
|
751 |
intermediate_size=28672, |
|
|
752 |
) |
|
|
753 |
] |
|
|
754 |
configs.extend(freewilly_2) |
|
|
755 |
|
|
|
756 |
|
|
|
757 |
################## |
|
|
758 |
# Meta Code Llama |
|
|
759 |
################## |
|
|
760 |
code_llama = [ |
|
|
761 |
# https://huggingface.co/codellama/CodeLlama-7b-hf/blob/main/config.json |
|
|
762 |
dict( |
|
|
763 |
name="CodeLlama-7b-hf", |
|
|
764 |
hf_config=dict(org="codellama", name="CodeLlama-7b-hf"), |
|
|
765 |
block_size=16384, |
|
|
766 |
vocab_size=32016, |
|
|
767 |
padding_multiple=16, |
|
|
768 |
n_layer=32, |
|
|
769 |
rotary_percentage=1.0, |
|
|
770 |
parallel_residual=False, |
|
|
771 |
bias=False, |
|
|
772 |
_norm_class="RMSNorm", |
|
|
773 |
norm_eps=1e-05, |
|
|
774 |
_mlp_class="LLaMAMLP", |
|
|
775 |
intermediate_size=11008, |
|
|
776 |
rope_base=1000000, |
|
|
777 |
), |
|
|
778 |
# https://huggingface.co/codellama/CodeLlama-13b-hf/blob/main/config.json |
|
|
779 |
dict( |
|
|
780 |
name="CodeLlama-13b-hf", |
|
|
781 |
hf_config=dict(org="codellama", name="CodeLlama-13b-hf"), |
|
|
782 |
block_size=16384, |
|
|
783 |
vocab_size=32016, |
|
|
784 |
padding_multiple=16, |
|
|
785 |
n_layer=40, |
|
|
786 |
n_head=40, |
|
|
787 |
n_embd=5120, |
|
|
788 |
rotary_percentage=1.0, |
|
|
789 |
parallel_residual=False, |
|
|
790 |
bias=False, |
|
|
791 |
_norm_class="RMSNorm", |
|
|
792 |
norm_eps=1e-05, |
|
|
793 |
_mlp_class="LLaMAMLP", |
|
|
794 |
intermediate_size=13824, |
|
|
795 |
rope_base=1000000, |
|
|
796 |
), |
|
|
797 |
# https://huggingface.co/codellama/CodeLlama-34b-hf/blob/main/config.json |
|
|
798 |
dict( |
|
|
799 |
name="CodeLlama-34b-hf", |
|
|
800 |
hf_config=dict(org="codellama", name="CodeLlama-34b-hf"), |
|
|
801 |
block_size=16384, |
|
|
802 |
vocab_size=32000, |
|
|
803 |
padding_multiple=64, |
|
|
804 |
n_layer=48, |
|
|
805 |
n_head=64, |
|
|
806 |
n_embd=8192, |
|
|
807 |
n_query_groups=8, |
|
|
808 |
rotary_percentage=1.0, |
|
|
809 |
parallel_residual=False, |
|
|
810 |
bias=False, |
|
|
811 |
_norm_class="RMSNorm", |
|
|
812 |
norm_eps=1e-05, |
|
|
813 |
_mlp_class="LLaMAMLP", |
|
|
814 |
intermediate_size=22016, |
|
|
815 |
rope_base=1000000, |
|
|
816 |
), |
|
|
817 |
# https://huggingface.co/codellama/CodeLlama-7b-Python-hf/blob/main/config.json |
|
|
818 |
dict( |
|
|
819 |
name="CodeLlama-7b-Python-hf", |
|
|
820 |
hf_config=dict(org="codellama", name="CodeLlama-7b-Python-hf"), |
|
|
821 |
block_size=16384, |
|
|
822 |
vocab_size=32000, |
|
|
823 |
padding_multiple=64, |
|
|
824 |
n_layer=32, |
|
|
825 |
rotary_percentage=1.0, |
|
|
826 |
parallel_residual=False, |
|
|
827 |
bias=False, |
|
|
828 |
_norm_class="RMSNorm", |
|
|
829 |
norm_eps=1e-05, |
|
|
830 |
_mlp_class="LLaMAMLP", |
|
|
831 |
intermediate_size=11008, |
|
|
832 |
rope_base=1000000, |
|
|
833 |
), |
|
|
834 |
# https://huggingface.co/codellama/CodeLlama-13b-Python-hf/blob/main/config.json |
|
|
835 |
dict( |
|
|
836 |
name="CodeLlama-13b-Python-hf", |
|
|
837 |
hf_config=dict(org="codellama", name="CodeLlama-13b-Python-hf"), |
|
|
838 |
block_size=16384, |
|
|
839 |
vocab_size=32000, |
|
|
840 |
padding_multiple=64, |
|
|
841 |
n_layer=40, |
|
|
842 |
n_head=40, |
|
|
843 |
n_embd=5120, |
|
|
844 |
rotary_percentage=1.0, |
|
|
845 |
parallel_residual=False, |
|
|
846 |
bias=False, |
|
|
847 |
_norm_class="RMSNorm", |
|
|
848 |
norm_eps=1e-05, |
|
|
849 |
_mlp_class="LLaMAMLP", |
|
|
850 |
intermediate_size=13824, |
|
|
851 |
rope_base=1000000, |
|
|
852 |
), |
|
|
853 |
# https://huggingface.co/codellama/CodeLlama-34b-Python-hf/blob/main/config.json |
|
|
854 |
dict( |
|
|
855 |
name="CodeLlama-34b-Python-hf", |
|
|
856 |
hf_config=dict(org="codellama", name="CodeLlama-34b-Python-hf"), |
|
|
857 |
block_size=16384, |
|
|
858 |
vocab_size=32000, |
|
|
859 |
padding_multiple=64, |
|
|
860 |
n_layer=48, |
|
|
861 |
n_head=64, |
|
|
862 |
n_embd=8192, |
|
|
863 |
n_query_groups=8, |
|
|
864 |
rotary_percentage=1.0, |
|
|
865 |
parallel_residual=False, |
|
|
866 |
bias=False, |
|
|
867 |
_norm_class="RMSNorm", |
|
|
868 |
norm_eps=1e-05, |
|
|
869 |
_mlp_class="LLaMAMLP", |
|
|
870 |
intermediate_size=22016, |
|
|
871 |
rope_base=1000000, |
|
|
872 |
), |
|
|
873 |
# https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf/tree/main/config.json |
|
|
874 |
dict( |
|
|
875 |
name="CodeLlama-7b-Instruct-hf", |
|
|
876 |
hf_config=dict(org="codellama", name="CodeLlama-7b-Instruct-hf"), |
|
|
877 |
block_size=16384, |
|
|
878 |
vocab_size=32016, |
|
|
879 |
padding_multiple=16, |
|
|
880 |
n_layer=32, |
|
|
881 |
rotary_percentage=1.0, |
|
|
882 |
parallel_residual=False, |
|
|
883 |
bias=False, |
|
|
884 |
_norm_class="RMSNorm", |
|
|
885 |
norm_eps=1e-05, |
|
|
886 |
_mlp_class="LLaMAMLP", |
|
|
887 |
intermediate_size=11008, |
|
|
888 |
rope_base=1000000, |
|
|
889 |
), |
|
|
890 |
# https://huggingface.co/codellama/CodeLlama-13b-Instruct-hf/blob/main/config.json |
|
|
891 |
dict( |
|
|
892 |
name="CodeLlama-13b-Instruct-hf", |
|
|
893 |
hf_config=dict(org="codellama", name="CodeLlama-13b-Instruct-hf"), |
|
|
894 |
block_size=2048, |
|
|
895 |
vocab_size=32016, |
|
|
896 |
padding_multiple=16, |
|
|
897 |
n_layer=40, |
|
|
898 |
n_head=40, |
|
|
899 |
n_embd=5120, |
|
|
900 |
rotary_percentage=1.0, |
|
|
901 |
parallel_residual=False, |
|
|
902 |
bias=False, |
|
|
903 |
_norm_class="RMSNorm", |
|
|
904 |
norm_eps=1e-05, |
|
|
905 |
_mlp_class="LLaMAMLP", |
|
|
906 |
intermediate_size=13824, |
|
|
907 |
rope_base=1000000, |
|
|
908 |
), |
|
|
909 |
# https://huggingface.co/codellama/CodeLlama-34b-Instruct-hf/blob/main/config.json |
|
|
910 |
dict( |
|
|
911 |
name="CodeLlama-34b-Instruct-hf", |
|
|
912 |
hf_config=dict(org="codellama", name="CodeLlama-34b-Instruct-hf"), |
|
|
913 |
block_size=16384, |
|
|
914 |
vocab_size=32000, |
|
|
915 |
padding_multiple=64, |
|
|
916 |
n_layer=48, |
|
|
917 |
n_head=64, |
|
|
918 |
n_embd=8192, |
|
|
919 |
n_query_groups=8, |
|
|
920 |
rotary_percentage=1.0, |
|
|
921 |
parallel_residual=False, |
|
|
922 |
bias=False, |
|
|
923 |
_norm_class="RMSNorm", |
|
|
924 |
norm_eps=1e-05, |
|
|
925 |
_mlp_class="LLaMAMLP", |
|
|
926 |
intermediate_size=22016, |
|
|
927 |
rope_base=1000000, |
|
|
928 |
), |
|
|
929 |
] |
|
|
930 |
configs.extend(code_llama) |
|
|
931 |
|
|
|
932 |
|
|
|
933 |
######################## |
|
|
934 |
# garage-bAInd Platypus |
|
|
935 |
######################## |
|
|
936 |
platypus = [ |
|
|
937 |
# https://huggingface.co/garage-bAInd/Platypus-30B/blob/main/config.json |
|
|
938 |
dict( |
|
|
939 |
name="Platypus-30B", |
|
|
940 |
hf_config=dict(org="garage-bAInd", name="Platypus-30B"), |
|
|
941 |
block_size=2048, |
|
|
942 |
padded_vocab_size=32000, |
|
|
943 |
n_layer=60, |
|
|
944 |
n_head=52, |
|
|
945 |
n_embd=6656, |
|
|
946 |
rotary_percentage=1.0, |
|
|
947 |
parallel_residual=False, |
|
|
948 |
bias=False, |
|
|
949 |
_norm_class="RMSNorm", |
|
|
950 |
norm_eps=1e-06, |
|
|
951 |
_mlp_class="LLaMAMLP", |
|
|
952 |
intermediate_size=17920, |
|
|
953 |
), |
|
|
954 |
# https://huggingface.co/garage-bAInd/Platypus2-7B/blob/main/config.json |
|
|
955 |
dict( |
|
|
956 |
name="Platypus2-7B", |
|
|
957 |
hf_config=dict(org="garage-bAInd", name="Platypus2-7B"), |
|
|
958 |
padded_vocab_size=32000, |
|
|
959 |
n_layer=32, |
|
|
960 |
rotary_percentage=1.0, |
|
|
961 |
parallel_residual=False, |
|
|
962 |
bias=False, |
|
|
963 |
_norm_class="RMSNorm", |
|
|
964 |
norm_eps=1e-05, |
|
|
965 |
_mlp_class="LLaMAMLP", |
|
|
966 |
intermediate_size=11008, |
|
|
967 |
), |
|
|
968 |
# https://huggingface.co/garage-bAInd/Platypus2-13B/blob/main/config.json |
|
|
969 |
dict( |
|
|
970 |
name="Platypus2-13B", |
|
|
971 |
hf_config=dict(org="garage-bAInd", name="Platypus2-13B"), |
|
|
972 |
padded_vocab_size=32000, |
|
|
973 |
n_layer=40, |
|
|
974 |
n_head=40, |
|
|
975 |
n_embd=5120, |
|
|
976 |
rotary_percentage=1.0, |
|
|
977 |
parallel_residual=False, |
|
|
978 |
bias=False, |
|
|
979 |
_norm_class="RMSNorm", |
|
|
980 |
norm_eps=1e-05, |
|
|
981 |
_mlp_class="LLaMAMLP", |
|
|
982 |
intermediate_size=13824, |
|
|
983 |
), |
|
|
984 |
# https://huggingface.co/garage-bAInd/Platypus2-70B/blob/main/config.json |
|
|
985 |
dict( |
|
|
986 |
name="Platypus2-70B", |
|
|
987 |
hf_config=dict(org="garage-bAInd", name="Platypus2-70B"), |
|
|
988 |
padded_vocab_size=32000, |
|
|
989 |
n_layer=80, |
|
|
990 |
n_head=64, |
|
|
991 |
n_embd=8192, |
|
|
992 |
rotary_percentage=1.0, |
|
|
993 |
parallel_residual=False, |
|
|
994 |
bias=False, |
|
|
995 |
_norm_class="RMSNorm", |
|
|
996 |
_mlp_class="LLaMAMLP", |
|
|
997 |
intermediate_size=28672, |
|
|
998 |
), |
|
|
999 |
# https://huggingface.co/garage-bAInd/Camel-Platypus2-13B/blob/main/config.json |
|
|
1000 |
dict( |
|
|
1001 |
name="Camel-Platypus2-13B", |
|
|
1002 |
hf_config=dict(org="garage-bAInd", name="Camel-Platypus2-13B"), |
|
|
1003 |
padded_vocab_size=32000, |
|
|
1004 |
n_layer=40, |
|
|
1005 |
n_head=40, |
|
|
1006 |
n_embd=5120, |
|
|
1007 |
rotary_percentage=1.0, |
|
|
1008 |
parallel_residual=False, |
|
|
1009 |
bias=False, |
|
|
1010 |
_norm_class="RMSNorm", |
|
|
1011 |
_mlp_class="LLaMAMLP", |
|
|
1012 |
intermediate_size=13824, |
|
|
1013 |
), |
|
|
1014 |
# https://huggingface.co/garage-bAInd/Camel-Platypus2-70B/blob/main/config.json |
|
|
1015 |
dict( |
|
|
1016 |
name="Camel-Platypus2-70B", |
|
|
1017 |
hf_config=dict(org="garage-bAInd", name="Camel-Platypus2-70B"), |
|
|
1018 |
padded_vocab_size=32000, |
|
|
1019 |
n_layer=80, |
|
|
1020 |
n_head=64, |
|
|
1021 |
n_embd=8192, |
|
|
1022 |
n_query_groups=8, |
|
|
1023 |
rotary_percentage=1.0, |
|
|
1024 |
parallel_residual=False, |
|
|
1025 |
bias=False, |
|
|
1026 |
_norm_class="RMSNorm", |
|
|
1027 |
_mlp_class="LLaMAMLP", |
|
|
1028 |
intermediate_size=28672, |
|
|
1029 |
), |
|
|
1030 |
# https://huggingface.co/garage-bAInd/Stable-Platypus2-13B/blob/main/config.json |
|
|
1031 |
dict( |
|
|
1032 |
name="Stable-Platypus2-13B", |
|
|
1033 |
hf_config=dict(org="garage-bAInd", name="Stable-Platypus2-13B"), |
|
|
1034 |
padded_vocab_size=32000, |
|
|
1035 |
n_layer=40, |
|
|
1036 |
n_head=40, |
|
|
1037 |
n_embd=5120, |
|
|
1038 |
rotary_percentage=1.0, |
|
|
1039 |
parallel_residual=False, |
|
|
1040 |
bias=False, |
|
|
1041 |
_norm_class="RMSNorm", |
|
|
1042 |
_mlp_class="LLaMAMLP", |
|
|
1043 |
intermediate_size=13824, |
|
|
1044 |
), |
|
|
1045 |
# https://huggingface.co/garage-bAInd/Platypus2-70B-instruct/blob/main/config.json |
|
|
1046 |
dict( |
|
|
1047 |
name="Platypus2-70B-instruct", |
|
|
1048 |
hf_config=dict(org="garage-bAInd", name="Platypus2-70B-instruct"), |
|
|
1049 |
padded_vocab_size=32000, |
|
|
1050 |
n_layer=80, |
|
|
1051 |
n_head=64, |
|
|
1052 |
n_embd=8192, |
|
|
1053 |
n_query_groups=8, |
|
|
1054 |
rotary_percentage=1.0, |
|
|
1055 |
parallel_residual=False, |
|
|
1056 |
bias=False, |
|
|
1057 |
_norm_class="RMSNorm", |
|
|
1058 |
_mlp_class="LLaMAMLP", |
|
|
1059 |
intermediate_size=28672, |
|
|
1060 |
), |
|
|
1061 |
] |
|
|
1062 |
configs.extend(platypus) |
|
|
1063 |
|
|
|
1064 |
|
|
|
1065 |
########################## |
|
|
1066 |
# Stability AI StableCode |
|
|
1067 |
########################## |
|
|
1068 |
stablecode = [ |
|
|
1069 |
# https://huggingface.co/stabilityai/stablecode-completion-alpha-3b/blob/main/config.json |
|
|
1070 |
dict( |
|
|
1071 |
name="stablecode-completion-alpha-3b", |
|
|
1072 |
hf_config=dict(org="stabilityai", name="stablecode-completion-alpha-3b"), |
|
|
1073 |
block_size=16384, |
|
|
1074 |
vocab_size=49152, |
|
|
1075 |
n_layer=32, |
|
|
1076 |
n_embd=2560, |
|
|
1077 |
), |
|
|
1078 |
# https://huggingface.co/stabilityai/stablecode-completion-alpha-3b-4k/blob/main/config.json |
|
|
1079 |
dict( |
|
|
1080 |
name="stablecode-completion-alpha-3b-4k", |
|
|
1081 |
hf_config=dict(org="stabilityai", name="stablecode-completion-alpha-3b-4k"), |
|
|
1082 |
vocab_size=49152, |
|
|
1083 |
n_layer=32, |
|
|
1084 |
n_embd=2560, |
|
|
1085 |
), |
|
|
1086 |
# https://huggingface.co/stabilityai/stablecode-instruct-alpha-3b/blob/main/config.json |
|
|
1087 |
dict( |
|
|
1088 |
name="stablecode-instruct-alpha-3b", |
|
|
1089 |
hf_config=dict(org="stabilityai", name="stablecode-instruct-alpha-3b"), |
|
|
1090 |
vocab_size=49152, |
|
|
1091 |
n_layer=32, |
|
|
1092 |
n_embd=2560, |
|
|
1093 |
), |
|
|
1094 |
] |
|
|
1095 |
configs.extend(stablecode) |
|
|
1096 |
|
|
|
1097 |
|
|
|
1098 |
################################## |
|
|
1099 |
# togethercomputer LLaMA-2-7B-32K |
|
|
1100 |
################################## |
|
|
1101 |
together_llama2_32k = [ |
|
|
1102 |
# https://huggingface.co/togethercomputer/LLaMA-2-7B-32K/blob/main/config.json |
|
|
1103 |
dict( |
|
|
1104 |
name="LLaMA-2-7B-32K", |
|
|
1105 |
hf_config=dict(org="togethercomputer", name="LLaMA-2-7B-32K"), |
|
|
1106 |
vocab_size=32000, |
|
|
1107 |
padding_multiple=64, |
|
|
1108 |
n_layer=32, |
|
|
1109 |
rotary_percentage=1.0, |
|
|
1110 |
parallel_residual=False, |
|
|
1111 |
bias=False, |
|
|
1112 |
_norm_class="RMSNorm", |
|
|
1113 |
_mlp_class="LLaMAMLP", |
|
|
1114 |
intermediate_size=11008, |
|
|
1115 |
rope_condense_ratio=8, |
|
|
1116 |
) |
|
|
1117 |
] |
|
|
1118 |
configs.extend(together_llama2_32k) |
|
|
1119 |
|
|
|
1120 |
|
|
|
1121 |
################ |
|
|
1122 |
# Microsoft Phi |
|
|
1123 |
################ |
|
|
1124 |
phi = [ |
|
|
1125 |
# https://huggingface.co/microsoft/phi-1_5/blob/main/config.json |
|
|
1126 |
dict( |
|
|
1127 |
name="phi-1_5", |
|
|
1128 |
hf_config=dict(org="microsoft", name="phi-1_5"), |
|
|
1129 |
vocab_size=50257, |
|
|
1130 |
padded_vocab_size=51200, |
|
|
1131 |
block_size=2048, |
|
|
1132 |
n_embd=2048, |
|
|
1133 |
n_layer=24, |
|
|
1134 |
rotary_percentage=0.5, # 32 / (n_embd / n_head) = 32 / 64 |
|
|
1135 |
shared_attention_norm=True, |
|
|
1136 |
lm_head_bias=True, |
|
|
1137 |
gelu_approximate="tanh", |
|
|
1138 |
) |
|
|
1139 |
] |
|
|
1140 |
configs.extend(phi) |
|
|
1141 |
|
|
|
1142 |
|
|
|
1143 |
############# |
|
|
1144 |
# Mistral AI |
|
|
1145 |
############# |
|
|
1146 |
mistral = [ |
|
|
1147 |
# https://huggingface.co/mistralai/Mistral-7B-v0.1/blob/main/config.json |
|
|
1148 |
dict( |
|
|
1149 |
name="Mistral-7B-{}v0.1", |
|
|
1150 |
hf_config=dict(org="mistralai", name="Mistral-7B-{}v0.1"), |
|
|
1151 |
padded_vocab_size=32000, |
|
|
1152 |
block_size=4096, # should be 32768 but sliding window attention is not implemented |
|
|
1153 |
n_layer=32, |
|
|
1154 |
n_query_groups=8, |
|
|
1155 |
rotary_percentage=1.0, |
|
|
1156 |
parallel_residual=False, |
|
|
1157 |
bias=False, |
|
|
1158 |
_norm_class="RMSNorm", |
|
|
1159 |
norm_eps=1e-05, |
|
|
1160 |
_mlp_class="LLaMAMLP", |
|
|
1161 |
intermediate_size=14336, |
|
|
1162 |
) |
|
|
1163 |
] |
|
|
1164 |
for c in mistral: |
|
|
1165 |
for kind in ("", "Instruct-"): |
|
|
1166 |
copy = deepcopy(c) |
|
|
1167 |
copy["name"] = c["name"].format(kind) |
|
|
1168 |
copy["hf_config"]["name"] = c["hf_config"]["name"].format(kind) |
|
|
1169 |
configs.append(copy) |
|
|
1170 |
|
|
|
1171 |
|
|
|
1172 |
############ |
|
|
1173 |
# TinyLlama |
|
|
1174 |
############ |
|
|
1175 |
tiny_llama = [ |
|
|
1176 |
dict( |
|
|
1177 |
name="tiny-llama-1.1b{}", |
|
|
1178 |
hf_config=dict(org="TinyLlama", name="TinyLlama-1.1B{}"), |
|
|
1179 |
block_size=2048, |
|
|
1180 |
vocab_size=32000, |
|
|
1181 |
padding_multiple=64, |
|
|
1182 |
n_layer=22, |
|
|
1183 |
n_head=32, |
|
|
1184 |
n_embd=2048, |
|
|
1185 |
rotary_percentage=1.0, |
|
|
1186 |
parallel_residual=False, |
|
|
1187 |
bias=False, |
|
|
1188 |
_norm_class="RMSNorm", # original TinyLlama uses FusedRMSNorm |
|
|
1189 |
norm_eps=1e-5, |
|
|
1190 |
_mlp_class="LLaMAMLP", |
|
|
1191 |
intermediate_size=5632, |
|
|
1192 |
n_query_groups=4, |
|
|
1193 |
), |
|
|
1194 |
] |
|
|
1195 |
for c in tiny_llama: |
|
|
1196 |
for kind, hf_postfix in (("", "-intermediate-step-955k-token-2T"), ("chat", "-Chat-v0.6")): |
|
|
1197 |
copy = deepcopy(c) |
|
|
1198 |
copy["name"] = c["name"].format(kind) |
|
|
1199 |
copy["hf_config"]["name"] = c["hf_config"]["name"].format(hf_postfix) |
|
|
1200 |
configs.append(copy) |
|
|
1201 |
|
|
|
1202 |
|
|
|
1203 |
name_to_config = {config["name"]: config for config in configs} |