Instructions to use ArthurZ/clef-flash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArthurZ/clef-flash with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ArthurZ/clef-flash", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download decision_head/config.json from ArthurZ/clef-flash: direct link, hf CLI and curl.
- Browser
- Download file 443 Bytes
-
https://huggingface.co/ArthurZ/clef-flash/resolve/main/decision_head/config.json
- Command line
-
hf download hf://ArthurZ/clef-flash/decision_head/config.json
-
curl -L -o config.json https://huggingface.co/ArthurZ/clef-flash/resolve/main/decision_head/config.json
443 Bytes
| { | |
| "architectures": [ | |
| "ClefDecisionHead" | |
| ], | |
| "attention_bias": true, | |
| "attention_dropout": 0.0, | |
| "backbone_hidden_size": 4096, | |
| "dtype": "bfloat16", | |
| "hidden_act": "gelu", | |
| "hidden_size": 1024, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "model_type": "clef", | |
| "num_attention_heads": 16, | |
| "num_evidence_layers": 2, | |
| "num_hidden_layers": 4, | |
| "num_key_value_heads": 16, | |
| "transformers_version": "5.19.0.dev0" | |
| } | |