Text Classification
Transformers
PyTorch
Safetensors
English
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use jantrienes/roberta-large-question-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jantrienes/roberta-large-question-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jantrienes/roberta-large-question-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jantrienes/roberta-large-question-classifier") model = AutoModelForSequenceClassification.from_pretrained("jantrienes/roberta-large-question-classifier") - Notebooks
- Google Colab
- Kaggle
File size: 1,195 Bytes
e8c0878 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | {
"_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": "extent",
"1": "disjunction",
"2": "concept",
"3": "comparison",
"4": "procedural",
"5": "consequence",
"6": "judgmental",
"7": "example",
"8": "verification",
"9": "cause"
},
"initializer_range": 0.02,
"intermediate_size": 4096,
"label2id": {
"cause": 9,
"comparison": 3,
"concept": 2,
"consequence": 5,
"disjunction": 1,
"example": 7,
"extent": 0,
"judgmental": 6,
"procedural": 4,
"verification": 8
},
"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": "single_label_classification",
"torch_dtype": "float32",
"transformers_version": "4.33.2",
"type_vocab_size": 1,
"use_cache": true,
"vocab_size": 50265
}
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