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import os
from concurrent.futures import ThreadPoolExecutor, as_completed
from huggingface_hub import snapshot_download
class ModelDownloader:
def __init__(self, max_workers_per_model=4):
# max_parallel_models > 1 は tqdm._lock が競合し異常終了するため、当面は1に固定する
self.max_parallel_models = 1
self.max_workers_per_model = max_workers_per_model
def _download_models(self, models_to_download):
def download_model(model_info):
kwargs = {
"repo_id": model_info["repo_id"],
"allow_patterns": model_info.get("allow_patterns", "*"),
"max_workers": self.max_workers_per_model,
}
snapshot_download(**kwargs)
with ThreadPoolExecutor(max_workers=self.max_parallel_models) as executor:
futures = [executor.submit(download_model, model) for model in models_to_download]
for future in as_completed(futures):
future.result()
def download_original(self):
self._download_models([
{"repo_id": "hunyuanvideo-community/HunyuanVideo", "allow_patterns": ["tokenizer/*", "tokenizer_2/*", "vae/*", "text_encoder/*", "text_encoder_2/*"]},
{"repo_id": "lllyasviel/flux_redux_bfl", "allow_patterns": ["feature_extractor/*", "image_encoder/*"]},
{"repo_id": "lllyasviel/FramePackI2V_HY"},
])
def download_f1(self):
self._download_models([
{"repo_id": "hunyuanvideo-community/HunyuanVideo", "allow_patterns": ["tokenizer/*", "tokenizer_2/*", "vae/*", "text_encoder/*", "text_encoder_2/*"]},
{"repo_id": "lllyasviel/flux_redux_bfl", "allow_patterns": ["feature_extractor/*", "image_encoder/*"]},
{"repo_id": "lllyasviel/FramePack_F1_I2V_HY_20250503"},
])
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