forked from phoenix-oss/llama-stack-mirror
97 lines
3.8 KiB
Python
97 lines
3.8 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import argparse
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import os
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import textwrap
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from pathlib import Path
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from huggingface_hub import snapshot_download
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from huggingface_hub.utils import GatedRepoError, RepositoryNotFoundError
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from llama_toolchain.cli.subcommand import Subcommand
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from llama_toolchain.utils import DEFAULT_DUMP_DIR
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DEFAULT_CHECKPOINT_DIR = os.path.join(DEFAULT_DUMP_DIR, "checkpoints")
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class Download(Subcommand):
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"""Llama cli for downloading llama toolchain assets"""
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def __init__(self, subparsers: argparse._SubParsersAction):
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super().__init__()
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self.parser = subparsers.add_parser(
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"download",
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prog="llama download",
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description="Download a model from the Hugging Face Hub",
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epilog=textwrap.dedent(
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"""\
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# Here are some examples on how to use this command:
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llama download --repo-id meta-llama/Llama-2-7b-hf --hf-token <HF_TOKEN>
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llama download --repo-id meta-llama/Llama-2-7b-hf --output-dir /data/my_custom_dir --hf-token <HF_TOKEN>
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HF_TOKEN=<HF_TOKEN> llama download --repo-id meta-llama/Llama-2-7b-hf
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The output directory will be used to load models and tokenizers for inference.
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"""
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),
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formatter_class=argparse.RawTextHelpFormatter,
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)
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self._add_arguments()
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self.parser.set_defaults(func=self._run_download_cmd)
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def _add_arguments(self):
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self.parser.add_argument(
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"repo_id",
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type=str,
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help="Name of the repository on Hugging Face Hub eg. llhf/Meta-Llama-3.1-70B-Instruct",
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)
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self.parser.add_argument(
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"--hf-token",
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type=str,
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required=False,
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default=os.getenv("HF_TOKEN", None),
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help="Hugging Face API token. Needed for gated models like Llama2. Will also try to read environment variable `HF_TOKEN` as default.",
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)
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self.parser.add_argument(
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"--ignore-patterns",
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type=str,
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required=False,
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default="*.safetensors",
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help="If provided, files matching any of the patterns are not downloaded. Defaults to ignoring "
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"safetensors files to avoid downloading duplicate weights.",
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)
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def _run_download_cmd(self, args: argparse.Namespace):
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model_name = args.repo_id.split("/")[-1]
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output_dir = Path(DEFAULT_CHECKPOINT_DIR) / model_name
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os.makedirs(output_dir, exist_ok=True)
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try:
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true_output_dir = snapshot_download(
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args.repo_id,
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local_dir=output_dir,
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# "auto" will download to cache_dir and symlink files to local_dir
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# avoiding unnecessary duplicate copies
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local_dir_use_symlinks="auto",
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ignore_patterns=args.ignore_patterns,
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token=args.hf_token,
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)
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except GatedRepoError:
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self.parser.error(
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"It looks like you are trying to access a gated repository. Please ensure you "
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"have access to the repository and have provided the proper Hugging Face API token "
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"using the option `--hf-token` or by running `huggingface-cli login`."
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"You can find your token by visiting https://huggingface.co/settings/tokens"
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)
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except RepositoryNotFoundError:
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self.parser.error(
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f"Repository '{args.repo_id}' not found on the Hugging Face Hub."
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)
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except Exception as e:
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self.parser.error(e)
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print(f"Successfully downloaded model to {true_output_dir}")
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