Instructions to use ankitdotpy/SVM_model_by_Group12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ankitdotpy/SVM_model_by_Group12 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ankitdotpy/SVM_model_by_Group12", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from ankitdotpy/SVM_model_by_Group12: direct link, hf CLI and curl.
- Browser
- Download file 96 Bytes
-
https://huggingface.co/ankitdotpy/SVM_model_by_Group12/resolve/main/config.json
- Command line
-
hf download hf://ankitdotpy/SVM_model_by_Group12/config.json
-
curl -L -o config.json https://huggingface.co/ankitdotpy/SVM_model_by_Group12/resolve/main/config.json
96 Bytes
| { | |
| "architecture": "SVM", | |
| "tokenizer": "TF-IDF", | |
| "num_classes": 3, | |
| "hidden_size": null | |
| } | |