mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-11-25 17:29:22 +01:00
113 lines
3.9 KiB
Python
113 lines
3.9 KiB
Python
'''
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Downloads models from Hugging Face to models/model-name.
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Example:
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python download-model.py facebook/opt-1.3b
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'''
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import argparse
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import multiprocessing
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import re
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import sys
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from pathlib import Path
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import requests
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import tqdm
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from bs4 import BeautifulSoup
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parser = argparse.ArgumentParser()
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parser.add_argument('MODEL', type=str)
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parser.add_argument('--branch', type=str, default='main', help='Name of the Git branch to download from.')
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parser.add_argument('--threads', type=int, default=1, help='Number of files to download simultaneously.')
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parser.add_argument('--text-only', action='store_true', help='Only download text files (txt/json).')
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args = parser.parse_args()
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def get_file(args):
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url = args[0]
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output_folder = args[1]
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idx = args[2]
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tot = args[3]
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print(f"Downloading file {idx} of {tot}...")
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r = requests.get(url, stream=True)
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with open(output_folder / Path(url.split('/')[-1]), 'wb') as f:
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total_size = int(r.headers.get('content-length', 0))
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block_size = 1024
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t = tqdm.tqdm(total=total_size, unit='iB', unit_scale=True)
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for data in r.iter_content(block_size):
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t.update(len(data))
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f.write(data)
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t.close()
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def sanitize_branch_name(branch_name):
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pattern = re.compile(r"^[a-zA-Z0-9._-]+$")
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if pattern.match(branch_name):
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return branch_name
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else:
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raise ValueError("Invalid branch name. Only alphanumeric characters, period, underscore and dash are allowed.")
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if __name__ == '__main__':
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model = args.MODEL
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if model[-1] == '/':
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model = model[:-1]
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branch = args.branch
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if args.branch is None:
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branch = 'main'
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else:
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try:
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branch_name = args.branch
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branch = sanitize_branch_name(branch_name)
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except ValueError as err_branch:
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print(f"Error: {err_branch}")
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sys.exit()
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url = f'https://huggingface.co/{model}/tree/{branch}'
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if branch != 'main':
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output_folder = Path("models") / (model.split('/')[-1] + f'_{branch}')
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else:
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output_folder = Path("models") / model.split('/')[-1]
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if not output_folder.exists():
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output_folder.mkdir()
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# Finding the relevant files to download
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page = requests.get(url)
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soup = BeautifulSoup(page.content, 'html.parser')
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links = soup.find_all('a')
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downloads = []
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classifications = []
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has_pytorch = False
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has_safetensors = False
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for link in links:
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href = link.get('href')[1:]
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if href.startswith(f'{model}/resolve/{branch}'):
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fname = Path(href).name
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is_pytorch = re.match("pytorch_model.*\.bin", fname)
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is_safetensors = re.match("model.*\.safetensors", fname)
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is_text = re.match(".*\.(txt|json)", fname)
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if is_text or is_safetensors or is_pytorch:
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if is_text:
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downloads.append(f'https://huggingface.co/{href}')
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classifications.append('text')
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continue
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if not args.text_only:
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downloads.append(f'https://huggingface.co/{href}')
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if is_safetensors:
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has_safetensors = True
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classifications.append('safetensors')
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elif is_pytorch:
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has_pytorch = True
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classifications.append('pytorch')
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# If both pytorch and safetensors are available, download safetensors only
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if has_pytorch and has_safetensors:
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for i in range(len(classifications)-1, -1, -1):
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if classifications[i] == 'pytorch':
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downloads.pop(i)
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# Downloading the files
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print(f"Downloading the model to {output_folder}")
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pool = multiprocessing.Pool(processes=args.threads)
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results = pool.map(get_file, [[downloads[i], output_folder, i+1, len(downloads)] for i in range(len(downloads))])
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pool.close()
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pool.join()
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