Text Classification
Transformers
ONNX
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use tmtryggingar/payment-codes-classifier-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tmtryggingar/payment-codes-classifier-dev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tmtryggingar/payment-codes-classifier-dev")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tmtryggingar/payment-codes-classifier-dev") model = AutoModelForSequenceClassification.from_pretrained("tmtryggingar/payment-codes-classifier-dev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/config.json from tmtryggingar/payment-codes-classifier-dev: direct link, hf CLI and curl.
- Browser
- Download file 2.21 kB
-
https://huggingface.co/tmtryggingar/payment-codes-classifier-dev/resolve/main/onnx/config.json
- Command line
-
hf download hf://tmtryggingar/payment-codes-classifier-dev/onnx/config.json
-
curl -L -o config.json https://huggingface.co/tmtryggingar/payment-codes-classifier-dev/resolve/main/onnx/config.json
2.21 kB
| { | |
| "architectures": [ | |
| "RobertaForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "eos_token_id": 2, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 1024, | |
| "id2label": { | |
| "0": "AKS", | |
| "1": "VIN-02", | |
| "2": "EFV", | |
| "3": "F\u00d6R", | |
| "4": "GLE", | |
| "5": "MEP", | |
| "6": "T\u00c6K", | |
| "7": "EFN", | |
| "8": "EIG", | |
| "9": "M\u00c1L", | |
| "10": "PLA", | |
| "11": "R\u00c9T", | |
| "12": "RY\u00d0", | |
| "13": "VAR", | |
| "14": "VIN", | |
| "15": "FRA", | |
| "16": "\u00cdSE", | |
| "17": "L\u00c6K", | |
| "18": "FLU", | |
| "19": "VI\u00d0", | |
| "20": "BIG", | |
| "21": "UBK", | |
| "22": "B\u00cdL", | |
| "23": "FRA-02", | |
| "24": "TJ\u00d3", | |
| "25": "SAM", | |
| "26": "ANN", | |
| "27": "RIT", | |
| "28": "\u00d6RM", | |
| "29": "GEY", | |
| "30": "SAB", | |
| "31": "VNT", | |
| "32": "\u00daRS", | |
| "33": "TRY", | |
| "34": "END-01", | |
| "35": "KIL", | |
| "36": "AFT", | |
| "37": "MUN", | |
| "38": "HJ\u00d3", | |
| "39": "S\u00c1L", | |
| "40": "SAL", | |
| "41": "UMV" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "label2id": { | |
| "AFT": 36, | |
| "AKS": 0, | |
| "ANN": 26, | |
| "BIG": 20, | |
| "B\u00cdL": 22, | |
| "EFN": 7, | |
| "EFV": 2, | |
| "EIG": 8, | |
| "END-01": 34, | |
| "FLU": 18, | |
| "FRA": 15, | |
| "FRA-02": 23, | |
| "F\u00d6R": 3, | |
| "GEY": 29, | |
| "GLE": 4, | |
| "HJ\u00d3": 38, | |
| "KIL": 35, | |
| "L\u00c6K": 17, | |
| "MEP": 5, | |
| "MUN": 37, | |
| "M\u00c1L": 9, | |
| "PLA": 10, | |
| "RIT": 27, | |
| "RY\u00d0": 12, | |
| "R\u00c9T": 11, | |
| "SAB": 30, | |
| "SAL": 40, | |
| "SAM": 25, | |
| "S\u00c1L": 39, | |
| "TJ\u00d3": 24, | |
| "TRY": 33, | |
| "T\u00c6K": 6, | |
| "UBK": 21, | |
| "UMV": 41, | |
| "VAR": 13, | |
| "VIN": 14, | |
| "VIN-02": 1, | |
| "VI\u00d0": 19, | |
| "VNT": 31, | |
| "\u00cdSE": 16, | |
| "\u00d6RM": 28, | |
| "\u00daRS": 32 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 514, | |
| "model_type": "roberta", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.55.4", | |
| "type_vocab_size": 1, | |
| "use_cache": true, | |
| "vocab_size": 50000 | |
| } | |