mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-09-19 15:56:56 +00:00
Make download-model.py importable
This commit is contained in:
oobabooga
parent
f91d3a3ff4
commit
34ec02d41d
@ -2,7 +2,7 @@
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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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python download_model.py facebook/opt-1.3b
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'''
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@ -19,6 +19,7 @@ import requests
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import tqdm
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from tqdm.contrib.concurrent import thread_map
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parser = argparse.ArgumentParser()
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parser.add_argument('MODEL', type=str, default=None, nargs='?')
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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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@ -30,40 +31,6 @@ parser.add_argument('--check', action='store_true', help='Validates the checksum
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args = parser.parse_args()
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def get_file(url, output_folder):
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filename = Path(url.rsplit('/', 1)[1])
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output_path = output_folder / filename
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if output_path.exists() and not args.clean:
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# Check if the file has already been downloaded completely
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r = requests.get(url, stream=True)
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total_size = int(r.headers.get('content-length', 0))
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if output_path.stat().st_size >= total_size:
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return
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# Otherwise, resume the download from where it left off
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headers = {'Range': f'bytes={output_path.stat().st_size}-'}
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mode = 'ab'
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else:
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headers = {}
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mode = 'wb'
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r = requests.get(url, stream=True, headers=headers)
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with open(output_path, mode) 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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with tqdm.tqdm(total=total_size, unit='iB', unit_scale=True, bar_format='{l_bar}{bar}| {n_fmt:6}/{total_fmt:6} {rate_fmt:6}') as t:
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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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def sanitize_branch_name(branch_name):
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pattern = re.compile(r"^[a-zA-Z0-9._-]+$")
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if pattern.match(branch_name):
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return branch_name
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else:
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raise ValueError("Invalid branch name. Only alphanumeric characters, period, underscore and dash are allowed.")
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def select_model_from_default_options():
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models = {
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"OPT 6.7B": ("facebook", "opt-6.7b", "main"),
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@ -110,7 +77,20 @@ EleutherAI/pythia-1.4b-deduped
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return model, branch
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def get_download_links_from_huggingface(model, branch):
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def sanitize_model_and_branch_names(model, branch):
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if model[-1] == '/':
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model = model[:-1]
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if branch is None:
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branch = "main"
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else:
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pattern = re.compile(r"^[a-zA-Z0-9._-]+$")
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if not pattern.match(branch):
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raise ValueError("Invalid branch name. Only alphanumeric characters, period, underscore and dash are allowed.")
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return model, branch
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def get_download_links_from_huggingface(model, branch, text_only=False):
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base = "https://huggingface.co"
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page = f"/api/models/{model}/tree/{branch}?cursor="
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cursor = b""
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@ -149,7 +129,7 @@ def get_download_links_from_huggingface(model, branch):
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links.append(f"https://huggingface.co/{model}/resolve/{branch}/{fname}")
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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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if not text_only:
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links.append(f"https://huggingface.co/{model}/resolve/{branch}/{fname}")
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if is_safetensors:
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has_safetensors = True
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@ -177,80 +157,114 @@ def get_download_links_from_huggingface(model, branch):
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return links, sha256, is_lora
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def download_files(file_list, output_folder, num_threads=8):
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thread_map(lambda url: get_file(url, output_folder), file_list, max_workers=num_threads, disable=True)
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if __name__ == '__main__':
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model = args.MODEL
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branch = args.branch
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if model is None:
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model, branch = select_model_from_default_options()
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else:
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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 branch is None:
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branch = "main"
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else:
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try:
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branch = sanitize_branch_name(branch)
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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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links, sha256, is_lora = get_download_links_from_huggingface(model, branch)
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if args.output is not None:
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base_folder = args.output
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else:
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def get_output_folder(model, branch, is_lora, base_folder=None):
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if base_folder is None:
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base_folder = 'models' if not is_lora else 'loras'
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output_folder = f"{'_'.join(model.split('/')[-2:])}"
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if branch != 'main':
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output_folder += f'_{branch}'
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output_folder = Path(base_folder) / output_folder
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return output_folder
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def get_single_file(url, output_folder, start_from_scratch=False):
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filename = Path(url.rsplit('/', 1)[1])
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output_path = output_folder / filename
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if output_path.exists() and not start_from_scratch:
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# Check if the file has already been downloaded completely
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r = requests.get(url, stream=True)
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total_size = int(r.headers.get('content-length', 0))
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if output_path.stat().st_size >= total_size:
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return
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# Otherwise, resume the download from where it left off
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headers = {'Range': f'bytes={output_path.stat().st_size}-'}
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mode = 'ab'
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else:
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headers = {}
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mode = 'wb'
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r = requests.get(url, stream=True, headers=headers)
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with open(output_path, mode) 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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with tqdm.tqdm(total=total_size, unit='iB', unit_scale=True, bar_format='{l_bar}{bar}| {n_fmt:6}/{total_fmt:6} {rate_fmt:6}') as t:
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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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def start_download_threads(file_list, output_folder, start_from_scratch=False, threads=1):
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thread_map(lambda url: get_single_file(url, output_folder, start_from_scratch=start_from_scratch), file_list, max_workers=threads, disable=True)
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def download_model_files(model, branch, links, sha256, output_folder, start_from_scratch=False, threads=1):
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# Creating the folder and writing the metadata
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if not output_folder.exists():
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output_folder.mkdir()
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with open(output_folder / 'huggingface-metadata.txt', 'w') as f:
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f.write(f'url: https://huggingface.co/{model}\n')
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f.write(f'branch: {branch}\n')
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f.write(f'download date: {str(datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"))}\n')
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sha256_str = ''
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for i in range(len(sha256)):
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sha256_str += f' {sha256[i][1]} {sha256[i][0]}\n'
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if sha256_str != '':
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f.write(f'sha256sum:\n{sha256_str}')
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# Downloading the files
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print(f"Downloading the model to {output_folder}")
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start_download_threads(links, output_folder, start_from_scratch=start_from_scratch, threads=threads)
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def check_model_files(model, branch, links, sha256, output_folder):
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# Validate the checksums
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validated = True
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for i in range(len(sha256)):
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fpath = (output_folder / sha256[i][0])
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if not fpath.exists():
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print(f"The following file is missing: {fpath}")
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validated = False
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continue
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with open(output_folder / sha256[i][0], "rb") as f:
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bytes = f.read()
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file_hash = hashlib.sha256(bytes).hexdigest()
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if file_hash != sha256[i][1]:
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print(f'Checksum failed: {sha256[i][0]} {sha256[i][1]}')
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validated = False
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else:
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print(f'Checksum validated: {sha256[i][0]} {sha256[i][1]}')
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if validated:
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print('[+] Validated checksums of all model files!')
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else:
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print('[-] Invalid checksums. Rerun download-model.py with the --clean flag.')
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if __name__ == '__main__':
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branch = args.branch
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model = args.MODEL
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if model is None:
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model, branch = select_model_from_default_options()
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# Cleaning up the model/branch names
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try:
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model, branch = sanitize_model_and_branch_names(model, branch)
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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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# Getting the download links from Hugging Face
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links, sha256, is_lora = get_download_links_from_huggingface(model, branch, text_only=args.text_only)
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# Getting the output folder
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output_folder = get_output_folder(model, branch, is_lora, base_folder=args.output)
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if args.check:
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# Validate the checksums
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validated = True
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for i in range(len(sha256)):
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fpath = (output_folder / sha256[i][0])
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if not fpath.exists():
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print(f"The following file is missing: {fpath}")
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validated = False
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continue
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with open(output_folder / sha256[i][0], "rb") as f:
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bytes = f.read()
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file_hash = hashlib.sha256(bytes).hexdigest()
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if file_hash != sha256[i][1]:
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print(f'Checksum failed: {sha256[i][0]} {sha256[i][1]}')
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validated = False
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else:
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print(f'Checksum validated: {sha256[i][0]} {sha256[i][1]}')
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if validated:
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print('[+] Validated checksums of all model files!')
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else:
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print('[-] Invalid checksums. Rerun download-model.py with the --clean flag.')
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# Check previously downloaded files
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check_model_files(model, branch, links, sha256, output_folder)
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else:
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# Creating the folder and writing the metadata
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if not output_folder.exists():
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output_folder.mkdir()
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with open(output_folder / 'huggingface-metadata.txt', 'w') as f:
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f.write(f'url: https://huggingface.co/{model}\n')
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f.write(f'branch: {branch}\n')
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f.write(f'download date: {str(datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"))}\n')
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sha256_str = ''
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for i in range(len(sha256)):
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sha256_str += f' {sha256[i][1]} {sha256[i][0]}\n'
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if sha256_str != '':
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f.write(f'sha256sum:\n{sha256_str}')
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# Downloading the files
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print(f"Downloading the model to {output_folder}")
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download_files(links, output_folder, args.threads)
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# Download files
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download_model_files(model, branch, links, sha256, output_folder, threads=args.threads)
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