Instructions to use Washedashore/Law with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use Washedashore/Law with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("undefined") model.load_adapter("Washedashore/Law", set_active=True) - Notebooks
- Google Colab
- Kaggle
| license: bigcode-openrail-m | |
| datasets: | |
| - amphora/QwQ-LongCoT-130K | |
| - 5CD-AI/LLaVA-CoT-o1-Instruct | |
| language: | |
| - en | |
| metrics: | |
| - accuracy | |
| - cer | |
| base_model: | |
| - answerdotai/ModernBERT-base | |
| new_version: meta-llama/Llama-3.3-70B-Instruct | |
| pipeline_tag: feature-extraction | |
| library_name: adapter-transformers | |