Instructions to use nielsr/coref-bert-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nielsr/coref-bert-large with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nielsr/coref-bert-large", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "attention_probs_dropout_prob": 0.1, | |
| "directionality": "bidi", | |
| "finetuning_task": null, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 1024, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "num_labels": 2, | |
| "output_attentions": false, | |
| "output_hidden_states": false, | |
| "output_past": true, | |
| "pooler_fc_size": 768, | |
| "pooler_num_attention_heads": 12, | |
| "pooler_num_fc_layers": 3, | |
| "pooler_size_per_head": 128, | |
| "pooler_type": "first_token_transform", | |
| "pruned_heads": {}, | |
| "torchscript": false, | |
| "type_vocab_size": 2, | |
| "use_bfloat16": false, | |
| "vocab_size": 28996 | |
| } | |