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import os | |
from huggingface_hub import hf_hub_download | |
REPO_ID = "tencent/HunyuanVideo-Avatar" | |
BASE_PATH = "ckpts" | |
LOCAL_BASE = os.path.join(os.getcwd(), "weights", "ckpts") | |
# List of essential files/folders to download (you can expand this if needed) | |
ESSENTIAL_PATHS = [ | |
# Transformers checkpoints | |
"hunyuan-video-t2v-720p/transformers/mp_rank_00_model_states_fp8.pt", | |
"hunyuan-video-t2v-720p/transformers/mp_rank_00_model_states.pt", | |
"hunyuan-video-t2v-720p/transformers/mp_rank_00_model_states_fp8_map.pt", | |
# VAE | |
"hunyuan-video-t2v-720p/vae/config.json", | |
"hunyuan-video-t2v-720p/vae/pytorch_model.pt", | |
# llava_llama_image shard files (adjust count if needed) | |
"llava_llama_image/model-00001-of-00004.safetensors", | |
"llava_llama_image/model-00002-of-00004.safetensors", | |
"llava_llama_image/model-00003-of-00004.safetensors", | |
"llava_llama_image/model-00004-of-00004.safetensors", | |
"llava_llama_image/config.json", | |
# text_encoder_2 | |
"text_encoder_2/config.json", | |
"text_encoder_2/pytorch_model.bin", | |
# whisper-tiny | |
"whisper-tiny/config.json", | |
"whisper-tiny/pytorch_model.bin", | |
"whisper-tiny/tokenizer.json", | |
"whisper-tiny/tokenizer_config.json", | |
"whisper-tiny/vocab.json", | |
# det_align | |
"det_align/config.json", | |
"det_align/pytorch_model.bin", | |
] | |
def download_files(): | |
for relative_path in ESSENTIAL_PATHS: | |
source_path = f"{BASE_PATH}/{relative_path}" | |
local_dir = os.path.join(LOCAL_BASE, os.path.dirname(relative_path)) | |
os.makedirs(local_dir, exist_ok=True) | |
print(f"β¬οΈ Downloading {source_path} ...") | |
try: | |
hf_hub_download( | |
repo_id=REPO_ID, | |
filename=source_path, | |
repo_type="model", | |
local_dir=local_dir, | |
local_dir_use_symlinks=False | |
) | |
except Exception as e: | |
print(f"β Failed to download {source_path}: {e}") | |
if __name__ == "__main__": | |
download_files() | |
print("\nβ All selected model weights downloaded to:") | |
print(f"{os.path.abspath(LOCAL_BASE)}") | |