Instructions to use readerbench/ro-offense-sequences with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use readerbench/ro-offense-sequences with Transformers:
# Load model directly from transformers import BERT_CRF model = BERT_CRF.from_pretrained("readerbench/ro-offense-sequences", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 698 Bytes
1344908 | 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 | {
"architectures": [
"BERT_CRF"
],
"attention_probs_dropout_prob": 0.1,
"bert_name": "readerbench/RoBERT-base",
"do_lower_case": 1,
"do_remove_accents": 0,
"dropout": 0.5,
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_name": "BERT_CRF",
"model_type": "BERT_CRF",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 0,
"torch_dtype": "float32",
"transformers_version": "4.34.0",
"type_vocab_size": 2,
"use_last_n_hidden_states": 7,
"vocab_size": 37788
}
|