It would be better if we provided a script for downloading the models. That way, people wouldn't have to install git-lfs and pull the model via git.
Here is an example script I used in the past to pull the public model from Hugging Face.

import argparse
import requests
import os
from tqdm import tqdm

def download_file(url, path):
    response = requests.get(url, stream=True)
    total_size_in_bytes = int(response.headers.get('content-length', 0))
    block_size = 1024 #1 Kbyte
    progress_bar = tqdm(total=total_size_in_bytes, unit='iB', unit_scale=True)

    with open(path, 'wb') as file:
        for data in response.iter_content(block_size):
            progress_bar.update(len(data))
            file.write(data)
            
    progress_bar.close()

def download_model(model_name, destination_folder="models"):
    # Define the base URL and headers for the Hugging Face API
    base_url = f"https://huggingface.co/{model_name}/resolve/main"
    headers = {"User-Agent": "Hugging Face Python"}

    # Send a GET request to the Hugging Face API to get a list of all files
    response = requests.get(f"https://huggingface.co/api/models/{model_name}", headers=headers)
    response.raise_for_status()
    
    # Extract the list of files from the response JSON
    files_to_download = [file["rfilename"] for file in response.json()["siblings"]]

    # Ensure the directory exists
    os.makedirs(f"{destination_folder}/{model_name}", exist_ok=True)

    # Download each file
    for file in files_to_download:
        print(f"Downloading {file}...")
        download_file(f"{base_url}/{file}", f"{destination_folder}/{model_name}/{file}")

if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument("model_name", type=str, help="Name of the model to download.")
    args = parser.parse_args()

    download_model(args.model_name)

Just run

python download.py <huggingface_model_name> .eg. mlx-community/Llama-2-7b-chat-mlx

Contribute Hugging Face models to the MLX Community #155

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