model_loader.py

from huggingface_hub import HfApi, HfFolder
import os
import os
from dotenv import load_dotenv

# Load environment variables from .env file if it exists
load_dotenv()

hf_token = os.getenv('HF_TOKEN')
api = HfApi()

# Specify the model details
model_id = "Testys/cnn_yor_ner"
sent_id = "Testys/cnn_sent_yor"
local_dir = "./my_model"
sent_dir = "./sent_model"

# Download the model folder
if not os.path.exists(local_dir):
    os.makedirs(local_dir)

    if not os.path.exists(os.path.join(local_dir, "pytorch_model.bin")):
        api.hf_hub_download(repo_id=model_id, filename="pytorch_model.bin", local_dir=local_dir, use_auth_token=hf_token)
    
    if not os.path.exists(os.path.join(local_dir, "config.json")):
        api.hf_hub_download(repo_id=model_id, filename="config.json", local_dir=local_dir, use_auth_token=hf_token)


# Check if the model is already downloaded
if not os.path.exists(sent_dir):
    os.makedirs(sent_dir) 
    
    # Download the model files only if they don't exist
    if not os.path.exists(os.path.join(sent_dir, "sent_pytorch_model.bin")):
        api.hf_hub_download(repo_id=sent_id, filename="sent_pytorch_model.bin", local_dir=sent_dir, use_auth_token=hf_token)
    if not os.path.exists(os.path.join(sent_dir, "config.json")):
        api.hf_hub_download(repo_id=sent_id, filename="config.json", local_dir=sent_dir, use_auth_token=hf_token)