Spaces:
Running
Running
File size: 1,926 Bytes
7e09504 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 |
#!/usr/bin/env python3
"""
Script to download the CSM-1B model from Hugging Face.
"""
import os
import sys
import logging
from huggingface_hub import hf_hub_download, login
from pathlib import Path
# Configure logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger(__name__)
def download_model():
"""Download the CSM-1B model."""
try:
# Set up paths
app_dir = Path("/app")
models_dir = app_dir / "models"
models_dir.mkdir(parents=True, exist_ok=True)
# Get token from environment
hf_token = os.environ.get("HF_TOKEN", "").strip()
# Try to login if token is provided
if hf_token:
logger.info("Logging in to Hugging Face...")
try:
login(token=hf_token)
logger.info("Successfully logged in to Hugging Face")
except Exception as e:
logger.error(f"Error logging in to Hugging Face: {e}")
logger.error("Will attempt to download without authentication")
else:
logger.warning("No Hugging Face token provided. Some models may not be accessible")
# Download the model
logger.info("Downloading CSM-1B model...")
model_path = hf_hub_download(
repo_id="sesame/csm-1b",
filename="ckpt.pt",
local_dir=str(models_dir),
token=hf_token if hf_token else None
)
logger.info(f"Model downloaded successfully to: {model_path}")
logger.info(f"File size: {os.path.getsize(model_path) / (1024*1024):.2f} MB")
return True
except Exception as e:
logger.error(f"Error downloading model: {e}")
return False
if __name__ == "__main__":
success = download_model()
sys.exit(0 if success else 1) |