Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
Portuguese
xlm-roberta
Generated from Trainer
Eval Results (legacy)
Instructions to use Luciano/xlm-roberta-large-finetuned-lener-br with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Luciano/xlm-roberta-large-finetuned-lener-br with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Luciano/xlm-roberta-large-finetuned-lener-br")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Luciano/xlm-roberta-large-finetuned-lener-br") model = AutoModelForTokenClassification.from_pretrained("Luciano/xlm-roberta-large-finetuned-lener-br", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "xlm-roberta-large", | |
| "architectures": [ | |
| "XLMRobertaForTokenClassification" | |
| ], | |
| "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": "O", | |
| "1": "B-ORGANIZACAO", | |
| "2": "I-ORGANIZACAO", | |
| "3": "B-PESSOA", | |
| "4": "I-PESSOA", | |
| "5": "B-TEMPO", | |
| "6": "I-TEMPO", | |
| "7": "B-LOCAL", | |
| "8": "I-LOCAL", | |
| "9": "B-LEGISLACAO", | |
| "10": "I-LEGISLACAO", | |
| "11": "B-JURISPRUDENCIA", | |
| "12": "I-JURISPRUDENCIA" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "label2id": { | |
| "B-JURISPRUDENCIA": 11, | |
| "B-LEGISLACAO": 9, | |
| "B-LOCAL": 7, | |
| "B-ORGANIZACAO": 1, | |
| "B-PESSOA": 3, | |
| "B-TEMPO": 5, | |
| "I-JURISPRUDENCIA": 12, | |
| "I-LEGISLACAO": 10, | |
| "I-LOCAL": 8, | |
| "I-ORGANIZACAO": 2, | |
| "I-PESSOA": 4, | |
| "I-TEMPO": 6, | |
| "O": 0 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 514, | |
| "model_type": "xlm-roberta", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "output_past": true, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.23.1", | |
| "type_vocab_size": 1, | |
| "use_cache": true, | |
| "vocab_size": 250002 | |
| } | |