Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Trained with AutoTrain
text-embeddings-inference
Instructions to use Defensa2025/C3ROBERTA8020 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Defensa2025/C3ROBERTA8020 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Defensa2025/C3ROBERTA8020")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Defensa2025/C3ROBERTA8020") model = AutoModelForSequenceClassification.from_pretrained("Defensa2025/C3ROBERTA8020", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "xlm-roberta-base", | |
| "_num_labels": 19, | |
| "architectures": [ | |
| "XLMRobertaForSequenceClassification" | |
| ], | |
| "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": 768, | |
| "id2label": { | |
| "0": "baloncesto, acb", | |
| "1": "baloncesto, champions-league", | |
| "2": "baloncesto, copa-rey", | |
| "3": "baloncesto, eurocup", | |
| "4": "baloncesto, euroliga", | |
| "5": "baloncesto, nba", | |
| "6": "futbol, champions-league", | |
| "7": "futbol, copa-rey", | |
| "8": "futbol, mas-futbol", | |
| "9": "futbol, primera-division", | |
| "10": "futbol, segunda-division", | |
| "11": "motor, dakar", | |
| "12": "motor, formula1", | |
| "13": "motor, motogp", | |
| "14": "motor, rallies", | |
| "15": "nan", | |
| "16": "polideportivo, ajedrez", | |
| "17": "polideportivo, boxeo", | |
| "18": "polideportivo, deportes-aventura" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "baloncesto, acb": 0, | |
| "baloncesto, champions-league": 1, | |
| "baloncesto, copa-rey": 2, | |
| "baloncesto, eurocup": 3, | |
| "baloncesto, euroliga": 4, | |
| "baloncesto, nba": 5, | |
| "futbol, champions-league": 6, | |
| "futbol, copa-rey": 7, | |
| "futbol, mas-futbol": 8, | |
| "futbol, primera-division": 9, | |
| "futbol, segunda-division": 10, | |
| "motor, dakar": 11, | |
| "motor, formula1": 12, | |
| "motor, motogp": 13, | |
| "motor, rallies": 14, | |
| "nan": 15, | |
| "polideportivo, ajedrez": 16, | |
| "polideportivo, boxeo": 17, | |
| "polideportivo, deportes-aventura": 18 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 514, | |
| "model_type": "xlm-roberta", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "output_past": true, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "problem_type": "single_label_classification", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.48.0", | |
| "type_vocab_size": 1, | |
| "use_cache": true, | |
| "vocab_size": 250002 | |
| } | |