mirror of
https://github.com/oobabooga/text-generation-webui.git
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55 lines
1.7 KiB
Python
55 lines
1.7 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 requests
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from bs4 import BeautifulSoup
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import multiprocessing
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import tqdm
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from sys import argv
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from pathlib import Path
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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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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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if __name__ == '__main__':
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model = argv[1]
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if model[-1] == '/':
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model = model[:-1]
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url = f'https://huggingface.co/{model}/tree/main'
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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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for link in links:
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href = link.get('href')[1:]
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if href.startswith(f'{model}/resolve/main'):
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if href.endswith(('.json', '.txt')) or (href.endswith('.bin') and 'pytorch_model' in href):
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downloads.append(f'https://huggingface.co/{href}')
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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=4)
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results = pool.map(get_file, [[downloads[i], output_folder] for i in range(len(downloads))])
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pool.close()
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pool.join()
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