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download_weights.py
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download_weights.py
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import argparse
from pathlib import Path
from huggingface_hub import hf_hub_download
import torch
ENCODEC_PATH = "https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th"
REMOTE_MODEL_PATHS = {
"text": {
"repo_id": "suno/bark",
"file_name": "text_2.pt",
},
"coarse": {
"repo_id": "suno/bark",
"file_name": "coarse_2.pt",
},
"fine": {
"repo_id": "suno/bark",
"file_name": "fine_2.pt",
},
}
parser = argparse.ArgumentParser()
parser.add_argument("--download-dir", type=str, required=True)
if __name__ == "__main__":
args = parser.parse_args()
out_dir = Path(args.download_dir)
out_dir.mkdir(parents=True, exist_ok=True)
print(" ### Downloading bark encoders...")
for model_k in REMOTE_MODEL_PATHS.keys():
model_details = REMOTE_MODEL_PATHS[model_k]
repo_id, filename = model_details["repo_id"], model_details["file_name"]
hf_hub_download(repo_id=repo_id, filename=filename, local_dir=out_dir)
print(" ### Downloading EnCodec weights...")
state_dict = torch.hub.load_state_dict_from_url(
ENCODEC_PATH,
map_location="cpu",
check_hash=True
)
with open(out_dir / Path(ENCODEC_PATH).name, "wb") as fout:
torch.save(state_dict, fout)
print("Done.")