vbatts/llama.cpp
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feat: Attempt to mirror the llama.cpp API for compatibility

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teleprint-me 2024-05-19 22:31:05 -04:00
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1 changed files with 36 additions and 33 deletions
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gguf-py/gguf/huggingface_hub.py
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@ -8,14 +8,17 @@ from hashlib import sha256
import requests import requests
from transformers import AutoTokenizer from transformers import AutoTokenizer
from .constants import MODEL_ARCH
class TokenizerType(IntEnum):
SPM = auto() # SentencePiece
BPE = auto() # BytePair
WPM = auto() # WordPiece
class ModelType(IntEnum): class LLaMaVocabType(IntEnum):
NON = auto() # For models without vocab
SPM = auto() # SentencePiece LLaMa tokenizer
BPE = auto() # BytePair GPT-2 tokenizer
WPM = auto() # WordPiece BERT tokenizer
class LLaMaModelType(IntEnum):
PTH = auto() # PyTorch PTH = auto() # PyTorch
SFT = auto() # SafeTensor SFT = auto() # SafeTensor
@ -26,28 +29,28 @@ class ModelType(IntEnum):
# - Use architecture types because they are explicitly defined # - Use architecture types because they are explicitly defined
# - Possible tokenizer model types are: SentencePiece, WordPiece, or BytePair # - Possible tokenizer model types are: SentencePiece, WordPiece, or BytePair
MODELS = ( MODELS = (
{"tokt": TokenizerType.SPM, "repo": "meta-llama/Llama-2-7b-hf", }, {"arch": MODEL_ARCH.LLAMA, "vocab_type": LLaMaVocabType.SPM, "repo": "meta-llama/Llama-2-7b-hf", },
{"tokt": TokenizerType.BPE, "repo": "meta-llama/Meta-Llama-3-8B", }, {"arch": MODEL_ARCH.LLAMA, "vocab_type": LLaMaVocabType.BPE, "repo": "meta-llama/Meta-Llama-3-8B", },
{"tokt": TokenizerType.SPM, "repo": "microsoft/Phi-3-mini-4k-instruct", }, {"arch": MODEL_ARCH.PHI3, "vocab_type": LLaMaVocabType.SPM, "repo": "microsoft/Phi-3-mini-4k-instruct", },
{"tokt": TokenizerType.BPE, "repo": "deepseek-ai/deepseek-llm-7b-base", }, {"arch": None, "vocab_type": LLaMaVocabType.BPE, "repo": "deepseek-ai/deepseek-llm-7b-base", },
{"tokt": TokenizerType.BPE, "repo": "deepseek-ai/deepseek-coder-6.7b-base", }, {"arch": None, "vocab_type": LLaMaVocabType.BPE, "repo": "deepseek-ai/deepseek-coder-6.7b-base", },
{"tokt": TokenizerType.BPE, "repo": "tiiuae/falcon-7b", }, {"arch": MODEL_ARCH.FALCON, "vocab_type": LLaMaVocabType.BPE, "repo": "tiiuae/falcon-7b", },
{"tokt": TokenizerType.WPM, "repo": "BAAI/bge-small-en-v1.5", }, {"arch": None, "vocab_type": LLaMaVocabType.WPM, "repo": "BAAI/bge-small-en-v1.5", },
{"tokt": TokenizerType.BPE, "repo": "mosaicml/mpt-7b", }, {"arch": MODEL_ARCH.MPT, "vocab_type": LLaMaVocabType.BPE, "repo": "mosaicml/mpt-7b", },
{"tokt": TokenizerType.BPE, "repo": "bigcode/starcoder2-3b", }, {"arch": MODEL_ARCH.STARCODER2, "vocab_type": LLaMaVocabType.BPE, "repo": "bigcode/starcoder2-3b", },
{"tokt": TokenizerType.BPE, "repo": "openai-community/gpt2", }, {"arch": MODEL_ARCH.GPT2, "vocab_type": LLaMaVocabType.BPE, "repo": "openai-community/gpt2", },
{"tokt": TokenizerType.BPE, "repo": "smallcloudai/Refact-1_6-base", }, {"arch": MODEL_ARCH.REFACT, "vocab_type": LLaMaVocabType.BPE, "repo": "smallcloudai/Refact-1_6-base", },
{"tokt": TokenizerType.BPE, "repo": "CohereForAI/c4ai-command-r-v01", }, {"arch": MODEL_ARCH.COMMAND_R, "vocab_type": LLaMaVocabType.BPE, "repo": "CohereForAI/c4ai-command-r-v01", },
{"tokt": TokenizerType.BPE, "repo": "Qwen/Qwen1.5-7B", }, {"arch": MODEL_ARCH.QWEN2, "vocab_type": LLaMaVocabType.BPE, "repo": "Qwen/Qwen1.5-7B", },
{"tokt": TokenizerType.BPE, "repo": "allenai/OLMo-1.7-7B-hf", }, {"arch": MODEL_ARCH.OLMO, "vocab_type": LLaMaVocabType.BPE, "repo": "allenai/OLMo-1.7-7B-hf", },
{"tokt": TokenizerType.BPE, "repo": "databricks/dbrx-base", }, {"arch": MODEL_ARCH.DBRX, "vocab_type": LLaMaVocabType.BPE, "repo": "databricks/dbrx-base", },
{"tokt": TokenizerType.WPM, "repo": "jinaai/jina-embeddings-v2-base-en", }, # WPM! {"arch": MODEL_ARCH.JINA_BERT_V2, "vocab_type": LLaMaVocabType.WPM, "repo": "jinaai/jina-embeddings-v2-base-en", },
{"tokt": TokenizerType.BPE, "repo": "jinaai/jina-embeddings-v2-base-es", }, {"arch": MODEL_ARCH.JINA_BERT_V2, "vocab_type": LLaMaVocabType.BPE, "repo": "jinaai/jina-embeddings-v2-base-es", },
{"tokt": TokenizerType.BPE, "repo": "jinaai/jina-embeddings-v2-base-de", }, {"arch": MODEL_ARCH.JINA_BERT_V2, "vocab_type": LLaMaVocabType.BPE, "repo": "jinaai/jina-embeddings-v2-base-de", },
{"tokt": TokenizerType.BPE, "repo": "microsoft/phi-1", }, {"arch": MODEL_ARCH.PHI2, "vocab_type": LLaMaVocabType.BPE, "repo": "microsoft/phi-1", },
{"tokt": TokenizerType.BPE, "repo": "stabilityai/stablelm-2-zephyr-1_6b", }, {"arch": MODEL_ARCH.STABLELM, "vocab_type": LLaMaVocabType.BPE, "repo": "stabilityai/stablelm-2-zephyr-1_6b", },
{"tokt": TokenizerType.SPM, "repo": "mistralai/Mistral-7B-Instruct-v0.2", }, {"arch": MODEL_ARCH.LLAMA, "vocab_type": LLaMaVocabType.SPM, "repo": "mistralai/Mistral-7B-Instruct-v0.2", },
{"tokt": TokenizerType.SPM, "repo": "mistralai/Mixtral-8x7B-Instruct-v0.1", }, {"arch": MODEL_ARCH.LLAMA, "vocab_type": LLaMaVocabType.SPM, "repo": "mistralai/Mixtral-8x7B-Instruct-v0.1", },
) )
@ -152,10 +155,10 @@ class HFVocabRequest(HFHubBase):
super().__init__(model_path, auth_token, logger) super().__init__(model_path, auth_token, logger)
@property @property
def tokenizer_type(self) -> TokenizerType: def tokenizer_type(self) -> LLaMaVocabType:
return TokenizerType return LLaMaVocabType
def resolve_filenames(self, tokt: TokenizerType) -> tuple[str]: def resolve_filenames(self, tokt: LLaMaVocabType) -> tuple[str]:
filenames = ["config.json", "tokenizer_config.json", "tokenizer.json"] filenames = ["config.json", "tokenizer_config.json", "tokenizer.json"]
if tokt == self.tokenizer_type.SPM: if tokt == self.tokenizer_type.SPM:
filenames.append("tokenizer.model") filenames.append("tokenizer.model")
@ -233,5 +236,5 @@ class HFModelRequest(HFHubBase):
super().__init__(model_path, auth_token, logger) super().__init__(model_path, auth_token, logger)
@property @property
def model_type(self) -> ModelType: def model_type(self) -> LLaMaModelType:
return ModelType return LLaMaModelType