Instructions to use klokedm/Micka-65k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use klokedm/Micka-65k with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("klokedm/Micka-65k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download usage_stats.py from klokedm/Micka-65k: direct link, hf CLI and curl.
- Browser
- Download file 792 Bytes
-
https://huggingface.co/klokedm/Micka-65k/resolve/main/usage_stats.py
- Command line
-
hf download hf://klokedm/Micka-65k/usage_stats.py
-
curl -L -o usage_stats.py https://huggingface.co/klokedm/Micka-65k/resolve/main/usage_stats.py
792 Bytes
| """Read Hugging Face's aggregate counters; no client usage collection is installed.""" | |
| from datetime import datetime, timezone | |
| import json | |
| from huggingface_hub import HfApi | |
| if __name__ == "__main__": | |
| info = HfApi().model_info("klokedm/Micka-65k", | |
| expand=["downloads", "downloadsAllTime", "likes", "lastModified"]) | |
| print(json.dumps(dict( | |
| repo="klokedm/Micka-65k", observed_at=datetime.now(timezone.utc).isoformat(), | |
| hub_downloads_last_30_days=info.downloads, hub_downloads_all_time=info.downloads_all_time, | |
| likes=info.likes, last_modified=info.last_modified.isoformat() if info.last_modified else None, | |
| limitation="Hub request counters are not unique users; tokenizer-only loads may be undercounted." | |
| ), indent=2)) | |