Instructions to use GRMenon/dp-roberta-large-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GRMenon/dp-roberta-large-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GRMenon/dp-roberta-large-finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GRMenon/dp-roberta-large-finetuned") model = AutoModelForSequenceClassification.from_pretrained("GRMenon/dp-roberta-large-finetuned") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "roberta-large", | |
| "architectures": [ | |
| "RobertaForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "eos_token_id": 2, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 1024, | |
| "id2label": { | |
| "0": "Social Proof", | |
| "1": "Misdirection", | |
| "2": "Urgency", | |
| "3": "Obstruction", | |
| "4": "Sneaking", | |
| "5": "Scarcity", | |
| "6": "Not Dark Pattern" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "label2id": { | |
| "Misdirection": 1, | |
| "Not Dark Pattern": 6, | |
| "Obstruction": 3, | |
| "Scarcity": 5, | |
| "Sneaking": 4, | |
| "Social Proof": 0, | |
| "Urgency": 2 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 514, | |
| "model_type": "roberta", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "problem_type": "multi_label_classification", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.36.2", | |
| "type_vocab_size": 1, | |
| "use_cache": false, | |
| "vocab_size": 50265 | |
| } | |