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
File size: 1,538 Bytes
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"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
}
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