Instructions to use BigTMiami/adapter_classifier_from_prtrained_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use BigTMiami/adapter_classifier_from_prtrained_test with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("roberta-base") model.load_adapter("BigTMiami/adapter_classifier_from_prtrained_test", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download head_config.json from BigTMiami/adapter_classifier_from_prtrained_test: direct link, hf CLI and curl.
- Browser
- Download file 440 Bytes
-
https://huggingface.co/BigTMiami/adapter_classifier_from_prtrained_test/resolve/main/head_config.json
- Command line
-
hf download hf://BigTMiami/adapter_classifier_from_prtrained_test/head_config.json
-
curl -L -o head_config.json https://huggingface.co/BigTMiami/adapter_classifier_from_prtrained_test/resolve/main/head_config.json
440 Bytes
| { | |
| "config": { | |
| "activation_function": "tanh", | |
| "bias": true, | |
| "dropout_prob": null, | |
| "head_type": "classification", | |
| "label2id": { | |
| "helpful": 1, | |
| "unhelpful": 0 | |
| }, | |
| "layers": 2, | |
| "num_labels": 2, | |
| "use_pooler": false | |
| }, | |
| "hidden_size": 768, | |
| "model_class": "RobertaAdapterModel", | |
| "model_name": "roberta-base", | |
| "model_type": "roberta", | |
| "name": "domain_training_test", | |
| "version": "0.1.2" | |
| } |