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scripts/setup
49 строк
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Iván Martínez
feat: Upgrade to LlamaIndex to 0.10 (#1663)
06 мар 2024, 19:51
Не верифицирован
06 мар 2024, 19:51
45f0571
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#!/usr/bin/env python3 import os import argparse from huggingface_hub import hf_hub_download, snapshot_download from transformers import AutoTokenizer from private_gpt.paths import models_path, models_cache_path from private_gpt.settings.settings import settings resume_download = True if __name__ == '__main__': parser = argparse.ArgumentParser(prog='Setup: Download models from huggingface') parser.add_argument('--resume', default=True, action=argparse.BooleanOptionalAction, help='Enable/Disable resume_download options to restart the download progress interrupted') args = parser.parse_args() resume_download = args.resume os.makedirs(models_path, exist_ok=True) # Download Embedding model embedding_path = models_path / "embedding" print(f"Downloading embedding {settings().huggingface.embedding_hf_model_name}") snapshot_download( repo_id=settings().huggingface.embedding_hf_model_name, cache_dir=models_cache_path, local_dir=embedding_path, ) print("Embedding model downloaded!") # Download LLM and create a symlink to the model file print(f"Downloading LLM {settings().llamacpp.llm_hf_model_file}") hf_hub_download( repo_id=settings().llamacpp.llm_hf_repo_id, filename=settings().llamacpp.llm_hf_model_file, cache_dir=models_cache_path, local_dir=models_path, resume_download=resume_download, ) print("LLM model downloaded!") # Download Tokenizer print(f"Downloading tokenizer {settings().llm.tokenizer}") AutoTokenizer.from_pretrained( pretrained_model_name_or_path=settings().llm.tokenizer, cache_dir=models_cache_path, ) print("Tokenizer downloaded!") print("Setup done")