Instructions to use jinmang2/textcnn-ko-dialect-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jinmang2/textcnn-ko-dialect-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jinmang2/textcnn-ko-dialect-classifier", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("jinmang2/textcnn-ko-dialect-classifier", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "jinmang2/textcnn-ko-dialect-classifier", | |
| "auto_map": { | |
| "AutoConfig": "configuration_textcnn.TextCNNConfig", | |
| "AutoModel": "modeling_textcnn.TextCNNModel", | |
| "AutoModelForSequenceClassification": "modeling_textcnn.TextCNNForSequenceClassification" | |
| }, | |
| "architectures": [ | |
| "TextCNNForSequenceClassification" | |
| ], | |
| "bos_token_id": 0, | |
| "dropout": 0.5, | |
| "embed_dim": 300, | |
| "eos_token_id": 1, | |
| "filter_sizes": [ | |
| 1, | |
| 2, | |
| 3, | |
| 4, | |
| 5 | |
| ], | |
| "id2label": { | |
| "0": "standard", | |
| "1": "dialect" | |
| }, | |
| "label2id": { | |
| "dialect": 1, | |
| "standard": 0 | |
| }, | |
| "num_filters": [ | |
| 128, | |
| 128, | |
| 128, | |
| 128, | |
| 128 | |
| ], | |
| "pad_token_id": 3, | |
| "transformers_version": "4.8.1", | |
| "vocab_size": 30000 | |
| } | |