Instructions to use danielachacon/roberta-peft-hatecheck with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use danielachacon/roberta-peft-hatecheck with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("roberta-large") model = PeftModel.from_pretrained(base_model, "danielachacon/roberta-peft-hatecheck") - Notebooks
- Google Colab
- Kaggle
Download adapter_config.json from danielachacon/roberta-peft-hatecheck: direct link, hf CLI and curl.
- Browser
- Download file 431 Bytes
-
https://huggingface.co/danielachacon/roberta-peft-hatecheck/resolve/main/adapter_config.json
- Command line
-
hf download hf://danielachacon/roberta-peft-hatecheck/adapter_config.json
-
curl -L -o adapter_config.json https://huggingface.co/danielachacon/roberta-peft-hatecheck/resolve/main/adapter_config.json
431 Bytes
| { | |
| "auto_mapping": null, | |
| "base_model_name_or_path": "roberta-large", | |
| "encoder_dropout": 0.0, | |
| "encoder_hidden_size": 128, | |
| "encoder_num_layers": 2, | |
| "encoder_reparameterization_type": "MLP", | |
| "inference_mode": true, | |
| "num_attention_heads": 16, | |
| "num_layers": 24, | |
| "num_transformer_submodules": 1, | |
| "num_virtual_tokens": 20, | |
| "peft_type": "P_TUNING", | |
| "revision": null, | |
| "task_type": "SEQ_CLS", | |
| "token_dim": 1024 | |
| } |