llama.cpp/gguf-py/scripts/hub-vocab.py

49 lines
1.5 KiB
Python

#!/usr/bin/env python3
from __future__ import annotations
import argparse
import logging
import os
import sys
from pathlib import Path
# Necessary to load the local gguf package
if "NO_LOCAL_GGUF" not in os.environ and (Path(__file__).parent.parent.parent / 'gguf-py').exists():
sys.path.insert(0, str(Path(__file__).parent.parent))
from gguf.constants import MODEL_ARCH, MODEL_ARCH_NAMES
from gguf.huggingface_hub import HFVocabRequest
logger = logging.getLogger("gguf-gen-pre")
def main():
parser = argparse.ArgumentParser()
parser.add_argument("hf_auth_token", help="A huggingface read auth token")
parser.add_argument(
"-v", "--verbose", action="store_true", help="Increase output verbosity."
)
parser.add_argument(
"-r", "--model-repo", default="meta-llama/Llama-2-7b-hf",
help="The models repository. Default is 'meta-llama/Llama-2-7b-hf'."
)
parser.add_argument(
"-m", "--model-path", default="models/",
help="The models storage path. Default is 'models/'."
)
parser.add_argument(
"--vocab-type",
const="BPE", nargs="?", choices=["BPE", "SPM"],
help="The type of vocab. Default is 'BPE'."
)
args = parser.parse_args()
vocab_request = HFVocabRequest(args.auth_token, args.model_path, logger)
vocab_type = vocab_request.get_vocab_enum(args.vocab_type)
vocab_request.get_all_vocab_files(args.model_repo, vocab_type)
if __name__ == '__main__':
main()