Token Classification
Transformers
Safetensors
English
roberta
sequence-labeling
political-science
social-groups
parliamentary-debates
Instructions to use maxwlnd/roberta_group_mention_detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maxwlnd/roberta_group_mention_detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="maxwlnd/roberta_group_mention_detector")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("maxwlnd/roberta_group_mention_detector") model = AutoModelForTokenClassification.from_pretrained("maxwlnd/roberta_group_mention_detector") - Notebooks
- Google Colab
- Kaggle
File size: 407 Bytes
b7488a4 2df5575 312efd9 13f7872 ae07f36 f4bccc0 b7488a4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"architectures": ["RobertaForTokenClassification"],
"model_type": "roberta",
"hidden_size": 768,
"id2label": {
"0": "B-socialgroup",
"1": "I-socialgroup",
"2": "O"
},
"label2id": {
"B-socialgroup": 0,
"I-socialgroup": 1,
"O": 2
},
"num_labels": 3,
"max_position_embeddings": 514,
"type_vocab_size": 1,
"vocab_size": 50265
} |