Instructions to use rafmacalaba/datause-extraction-v6-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rafmacalaba/datause-extraction-v6-finetuned with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rafmacalaba/datause-extraction-v6-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from rafmacalaba/datause-extraction-v6-finetuned: direct link, hf CLI and curl.
- Browser
- Download file 254 Bytes
-
https://huggingface.co/rafmacalaba/datause-extraction-v6-finetuned/resolve/main/config.json
- Command line
-
hf download hf://rafmacalaba/datause-extraction-v6-finetuned/config.json
-
curl -L -o config.json https://huggingface.co/rafmacalaba/datause-extraction-v6-finetuned/resolve/main/config.json
254 Bytes
| { | |
| "_attn_implementation_autoset": true, | |
| "counting_layer": "count_lstm", | |
| "max_width": 8, | |
| "model_name": "microsoft/deberta-v3-large", | |
| "model_type": "extractor", | |
| "token_pooling": "first", | |
| "transformers_version": "4.57.3", | |
| "use_moe": false | |
| } | |