Text Classification
Transformers
Safetensors
Korean
bert
klue
korean
minwon
complaint
public-administration
text-embeddings-inference
Instructions to use atti433/minde-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use atti433/minde-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="atti433/minde-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("atti433/minde-classifier") model = AutoModelForSequenceClassification.from_pretrained("atti433/minde-classifier") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "klue/bert-base", | |
| "architectures": [ | |
| "BertForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "classifier_dropout": null, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "\uad50\ud1b5", | |
| "1": "\uac74\ucd95", | |
| "2": "\ud589\uc815", | |
| "3": "\ubcf4\uac74\uc704\uc0dd", | |
| "4": "\ud658\uacbd", | |
| "5": "\ubb38\ud654_\uc5ec\uac00", | |
| "6": "\ub18d\ucd95\uc0b0", | |
| "7": "\ubcf5\uc9c0", | |
| "8": "\uc138\ubb34", | |
| "9": "\uc0c1\ud558\uc218\ub3c4", | |
| "10": "\uacbd\uc81c" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "\uac74\ucd95": 1, | |
| "\uacbd\uc81c": 10, | |
| "\uad50\ud1b5": 0, | |
| "\ub18d\ucd95\uc0b0": 6, | |
| "\ubb38\ud654_\uc5ec\uac00": 5, | |
| "\ubcf4\uac74\uc704\uc0dd": 3, | |
| "\ubcf5\uc9c0": 7, | |
| "\uc0c1\ud558\uc218\ub3c4": 9, | |
| "\uc138\ubb34": 8, | |
| "\ud589\uc815": 2, | |
| "\ud658\uacbd": 4 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "absolute", | |
| "problem_type": "single_label_classification", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.46.3", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 32009 | |
| } | |