Instructions to use ishaan1402/cbt-thought-pattern-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ishaan1402/cbt-thought-pattern-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ishaan1402/cbt-thought-pattern-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ishaan1402/cbt-thought-pattern-classifier") model = AutoModelForSequenceClassification.from_pretrained("ishaan1402/cbt-thought-pattern-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "RobertaForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "eos_token_id": 2, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 1024, | |
| "id2label": { | |
| "0": "Catastrophizing", | |
| "1": "Discounting the positive", | |
| "2": "Labeling and mislabeling", | |
| "3": "Mental filtering", | |
| "4": "Jumping to conclusions: mind reading", | |
| "5": "Jumping to conclusions: Fortune-telling", | |
| "6": "Overgeneralization", | |
| "7": "Personalization", | |
| "8": "Black-and-white or polarized thinking / All or nothing thinking", | |
| "9": "Should statements", | |
| "10": "None" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "is_decoder": false, | |
| "label2id": { | |
| "Black-and-white or polarized thinking / All or nothing thinking": 8, | |
| "Catastrophizing": 0, | |
| "Discounting the positive": 1, | |
| "Jumping to conclusions: Fortune-telling": 5, | |
| "Jumping to conclusions: mind reading": 4, | |
| "Labeling and mislabeling": 2, | |
| "Mental filtering": 3, | |
| "None": 10, | |
| "Overgeneralization": 6, | |
| "Personalization": 7, | |
| "Should statements": 9 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 514, | |
| "model_type": "roberta", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "pad_token_id": 1, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.0.0", | |
| "type_vocab_size": 1, | |
| "use_cache": true, | |
| "vocab_size": 50265 | |
| } | |