Instructions to use mateoopa/bank-categorizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mateoopa/bank-categorizer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mateoopa/bank-categorizer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mateoopa/bank-categorizer") model = AutoModelForSequenceClassification.from_pretrained("mateoopa/bank-categorizer") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "BertForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": null, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "eos_token_id": null, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "AWS", | |
| "1": "Arriendo", | |
| "2": "Colegio Migue", | |
| "3": "Cuido Zeus", | |
| "4": "Gasolina", | |
| "5": "Gasto Materiales Construcci\u00f3n", | |
| "6": "Gasto mano de obra", | |
| "7": "Huevos - mercado", | |
| "8": "Lunch oficina", | |
| "9": "Mercado (supermercado)", | |
| "10": "Nomina LT", | |
| "11": "Nomina RV", | |
| "12": "Pago Ail\u00edn", | |
| "13": "Parqueaderos", | |
| "14": "Proteina carne/pollo", | |
| "15": "Salidas con pap\u00e1 Ail\u00edn", | |
| "16": "Salidas/entretenimiento", | |
| "17": "Servicios P\u00fablicos EPM", | |
| "18": "Suscripciones", | |
| "19": "Verduras - Mercado" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "is_decoder": false, | |
| "label2id": { | |
| "AWS": 0, | |
| "Arriendo": 1, | |
| "Colegio Migue": 2, | |
| "Cuido Zeus": 3, | |
| "Gasolina": 4, | |
| "Gasto Materiales Construcci\u00f3n": 5, | |
| "Gasto mano de obra": 6, | |
| "Huevos - mercado": 7, | |
| "Lunch oficina": 8, | |
| "Mercado (supermercado)": 9, | |
| "Nomina LT": 10, | |
| "Nomina RV": 11, | |
| "Pago Ail\u00edn": 12, | |
| "Parqueaderos": 13, | |
| "Proteina carne/pollo": 14, | |
| "Salidas con pap\u00e1 Ail\u00edn": 15, | |
| "Salidas/entretenimiento": 16, | |
| "Servicios P\u00fablicos EPM": 17, | |
| "Suscripciones": 18, | |
| "Verduras - Mercado": 19 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "output_past": true, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "problem_type": "single_label_classification", | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.10.2", | |
| "type_vocab_size": 2, | |
| "use_cache": false, | |
| "vocab_size": 31002 | |
| } | |