Any-to-Any
Transformers
Safetensors
neo_chat
image-feature-extraction
multimodal
text-to-image
image-to-text
image-editing
interleaved-generation
custom_code
Instructions to use sensenova/SenseNova-U1-8B-MoT-SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sensenova/SenseNova-U1-8B-MoT-SFT with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sensenova/SenseNova-U1-8B-MoT-SFT", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| #!/usr/bin/env python3 | |
| """Upload this directory to Hugging Face (excludes .git). Run from repo root or pass --dir.""" | |
| import argparse | |
| import os | |
| from huggingface_hub import HfApi, login | |
| def main(): | |
| p = argparse.ArgumentParser() | |
| p.add_argument( | |
| "--dir", | |
| default=os.path.dirname(os.path.abspath(__file__)), | |
| help="Folder to upload (default: this script's directory)", | |
| ) | |
| p.add_argument( | |
| "--repo-id", | |
| default="sensenova/SenseNova-U1-Mini-SFT", | |
| ) | |
| args = p.parse_args() | |
| token = os.environ.get("HF_TOKEN") or os.environ.get("HUGGING_FACE_HUB_TOKEN") | |
| if token: | |
| login(token=token) | |
| else: | |
| login() | |
| HfApi().upload_folder( | |
| folder_path=args.dir, | |
| repo_id=args.repo_id, | |
| repo_type="model", | |
| ignore_patterns=[".git/**"], | |
| ) | |
| print("Done:", args.repo_id) | |
| if __name__ == "__main__": | |
| main() |