Downloading Large LFS Files
I am trying to download few models which are very heavy and have LFS files. for this i was using dask for  parallelization. But the code is not able to download the model and suggest the model name is not availableo on git, here is the code used . Can someone suggest how to download multiple large LFS files and not use git clone as it could be very slowimport daskfrom dask.diagnostics import ProgressBarimport huggingface_hubimport timeimport osimport subprocessfrom huggingface_hub import REDACTED_TOKEN_downloadYour Hugging Face token (replace with your actual token)token = “your_actual_token”Model IDsmodel_ids = [“lysandre/arxiv-nlp”, “tiiuae/falcon-180B”]def download_model(model_id):start_time = time.time()try:# Download the model metadata (including LFS pointers)REDACTED_TOKEN_download(repo_id=model_id, token=token, cache_dir=‘/path/to/your/directory’)# Change to the directory where the model is downloaded
    model_dir = os.path.join('/path/to/your/directory', model_id)
    os.chdir(model_dir)

    # Run git-lfs fetch to download the LFS files
    subprocess.run(["git", "lfs", "fetch", "--all"], check=True)
    subprocess.run(["git", "lfs", "checkout"], check=True)
except Exception as e:
    print(f"Error downloading {model_id}: {e}")
elapsed_time = time.time() - start_time
print(f"Downloaded {model_id} in {elapsed_time:.2f} seconds")Create a Dask list of delayed objects for each model informationmodel_infos = [dask.delayed(download_model)(model_id) for model_id in model_ids]Download models in parallel and track progresswith ProgressBar():dask.compute(model_infos)