Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use exala-e/db_himp_4.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use exala-e/db_himp_4.2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="exala-e/db_himp_4.2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("exala-e/db_himp_4.2") model = AutoModelForSequenceClassification.from_pretrained("exala-e/db_himp_4.2") - Notebooks
- Google Colab
- Kaggle
| { | |
| "activation": "gelu", | |
| "architectures": [ | |
| "DistilBertForSequenceClassification" | |
| ], | |
| "attention_dropout": 0.2, | |
| "bos_token_id": null, | |
| "dim": 768, | |
| "dropout": 0.18, | |
| "dtype": "float32", | |
| "eos_token_id": null, | |
| "hidden_dim": 3072, | |
| "id2label": { | |
| "0": "AD", | |
| "1": "AM", | |
| "2": "B", | |
| "3": "BDNC", | |
| "4": "BENE", | |
| "5": "BN", | |
| "6": "BOT", | |
| "7": "CB", | |
| "8": "CE", | |
| "9": "COM", | |
| "10": "CONF", | |
| "11": "CQ", | |
| "12": "DNC", | |
| "13": "FD", | |
| "14": "GNI", | |
| "15": "H", | |
| "16": "HOLD", | |
| "17": "HOW", | |
| "18": "HR", | |
| "19": "HRN-", | |
| "20": "LB", | |
| "21": "N", | |
| "22": "N-", | |
| "23": "NE", | |
| "24": "NG", | |
| "25": "NO", | |
| "26": "NQD", | |
| "27": "OI", | |
| "28": "P", | |
| "29": "PCOST", | |
| "30": "PG", | |
| "31": "PG+", | |
| "32": "PN", | |
| "33": "PNI", | |
| "34": "PO", | |
| "35": "PONI", | |
| "36": "POOR", | |
| "37": "Q", | |
| "38": "R", | |
| "39": "RICH", | |
| "40": "SCAM", | |
| "41": "SEC", | |
| "42": "TC", | |
| "43": "TELE", | |
| "44": "TMC", | |
| "45": "U" | |
| }, | |
| "initializer_range": 0.02, | |
| "label2id": { | |
| "AD": 0, | |
| "AM": 1, | |
| "B": 2, | |
| "BDNC": 3, | |
| "BENE": 4, | |
| "BN": 5, | |
| "BOT": 6, | |
| "CB": 7, | |
| "CE": 8, | |
| "COM": 9, | |
| "CONF": 10, | |
| "CQ": 11, | |
| "DNC": 12, | |
| "FD": 13, | |
| "GNI": 14, | |
| "H": 15, | |
| "HOLD": 16, | |
| "HOW": 17, | |
| "HR": 18, | |
| "HRN-": 19, | |
| "LB": 20, | |
| "N": 21, | |
| "N-": 22, | |
| "NE": 23, | |
| "NG": 24, | |
| "NO": 25, | |
| "NQD": 26, | |
| "OI": 27, | |
| "P": 28, | |
| "PCOST": 29, | |
| "PG": 30, | |
| "PG+": 31, | |
| "PN": 32, | |
| "PNI": 33, | |
| "PO": 34, | |
| "PONI": 35, | |
| "POOR": 36, | |
| "Q": 37, | |
| "R": 38, | |
| "RICH": 39, | |
| "SCAM": 40, | |
| "SEC": 41, | |
| "TC": 42, | |
| "TELE": 43, | |
| "TMC": 44, | |
| "U": 45 | |
| }, | |
| "max_position_embeddings": 512, | |
| "model_type": "distilbert", | |
| "n_heads": 12, | |
| "n_layers": 6, | |
| "pad_token_id": 0, | |
| "qa_dropout": 0.1, | |
| "seq_classif_dropout": 0.2, | |
| "sinusoidal_pos_embds": false, | |
| "tie_weights_": true, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.12.1", | |
| "use_cache": false, | |
| "vocab_size": 30522 | |
| } | |