Text Classification
Transformers
Safetensors
deberta-v2
citation-function-classification
scholarly-positioning
related-work-generation
rwgbench
multicite
text-embeddings-inference
Instructions to use BFTree/rwgbench-citation-frame-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BFTree/rwgbench-citation-frame-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BFTree/rwgbench-citation-frame-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BFTree/rwgbench-citation-frame-classifier") model = AutoModelForSequenceClassification.from_pretrained("BFTree/rwgbench-citation-frame-classifier") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "microsoft/deberta-v3-large", | |
| "architectures": [ | |
| "DebertaV2ForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 1024, | |
| "id2label": { | |
| "0": "motivation", | |
| "1": "background", | |
| "2": "uses", | |
| "3": "extends", | |
| "4": "similarities", | |
| "5": "differences", | |
| "6": "future_work" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "label2id": { | |
| "background": 1, | |
| "differences": 5, | |
| "extends": 3, | |
| "future_work": 6, | |
| "motivation": 0, | |
| "similarities": 4, | |
| "uses": 2 | |
| }, | |
| "layer_norm_eps": 1e-07, | |
| "max_position_embeddings": 512, | |
| "max_relative_positions": -1, | |
| "model_type": "deberta-v2", | |
| "norm_rel_ebd": "layer_norm", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "pad_token_id": 0, | |
| "pooler_dropout": 0, | |
| "pooler_hidden_act": "gelu", | |
| "pooler_hidden_size": 1024, | |
| "pos_att_type": [ | |
| "p2c", | |
| "c2p" | |
| ], | |
| "position_biased_input": false, | |
| "position_buckets": 256, | |
| "problem_type": "multi_label_classification", | |
| "relative_attention": true, | |
| "share_att_key": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.43.1", | |
| "type_vocab_size": 0, | |
| "vocab_size": 128100 | |
| } | |