Instructions to use MeTask-Rain/MetaDecision-31B-Rain-v2.3d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MeTask-Rain/MetaDecision-31B-Rain-v2.3d with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Download service/model_setup.py from MeTask-Rain/MetaDecision-31B-Rain-v2.3d: direct link, hf CLI and curl.
- Browser
- Download file 650 Bytes
-
https://huggingface.co/MeTask-Rain/MetaDecision-31B-Rain-v2.3d/resolve/main/service/model_setup.py
- Command line
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hf download hf://MeTask-Rain/MetaDecision-31B-Rain-v2.3d/service/model_setup.py
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curl -L -o model_setup.py https://huggingface.co/MeTask-Rain/MetaDecision-31B-Rain-v2.3d/resolve/main/service/model_setup.py
650 Bytes
| """Report a missing processor config in the model folder; never downloads or copies.""" | |
| from pathlib import Path | |
| # Gemma 4 keeps its processor settings in processor_config.json; the checkpoint has no | |
| # preprocessor_config.json or video_preprocessor_config.json and needs neither. | |
| NAMES=('processor_config.json',) | |
| def report_processor_configs(model_dir): | |
| """Print nothing for a complete model folder; return the missing names.""" | |
| p=Path(model_dir) | |
| missing=[n for n in NAMES if not (p/n).is_file()] | |
| if missing: | |
| print('[model_setup] processor config not in the model folder: '+', '.join(missing),flush=True) | |
| return missing | |