Campus-AI / scripts /deploy_to_hf.py
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Final Release: CampusGen AI Pipeline & Compositor
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import os
import sys
from huggingface_hub import HfApi, login
def deploy_model():
print("="*60)
print(" CAMPUS AI - HUGGING FACE DEPLOYMENT")
print("="*60)
# 1. Ask for credentials and repo ID
hf_token = input("\nEnter your Hugging Face WRITE Token (paste and press Enter): ").strip()
repo_id = input("Enter your Hugging Face Repository ID (e.g. your_username/campus-ai-poster-sdxl): ").strip()
if not hf_token or not repo_id:
print("\n[!] Error: Token and Repository ID are required.")
sys.exit(1)
try:
# 2. Authenticate
print("\n[+] Authenticating with Hugging Face...")
login(token=hf_token)
api = HfApi()
# 3. Verify Phase 3 Model exists
model_dir = "models/sdxl/checkpoints/campus_ai_poster_sdxl_phase3"
model_file = os.path.join(model_dir, "campus_ai_poster_sdxl_phase3.safetensors")
if not os.path.exists(model_file):
print(f"\n[!] Error: Phase 3 model not found at {model_file}!")
print("Make sure Phase 3 training has finished successfully.")
sys.exit(1)
print("\n[+] Creating/Verifying repository...")
api.create_repo(repo_id=repo_id, exist_ok=True, private=False)
# 4. Upload the model
print(f"\n[+] Uploading Phase 3 Model to {repo_id}...")
api.upload_file(
path_or_fileobj=model_file,
path_in_repo="campus_ai_poster_sdxl_phase3.safetensors",
repo_id=repo_id,
repo_type="model",
commit_message="Upload final Campus AI Phase 3 LoRA weights"
)
print("\n" + "="*60)
print(f" ✅ DEPLOYMENT SUCCESSFUL!")
print(f" Model is now live at: https://huggingface.co/{repo_id}")
print("="*60)
print("You can now connect this model directly to your Hugging Face space.")
except Exception as e:
print(f"\n[!] Deployment Failed: {str(e)}")
if __name__ == "__main__":
deploy_model()