Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use hyunkookim/roberta-base-klue-ynat-classification-using-hg_api-epoch_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hyunkookim/roberta-base-klue-ynat-classification-using-hg_api-epoch_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hyunkookim/roberta-base-klue-ynat-classification-using-hg_api-epoch_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hyunkookim/roberta-base-klue-ynat-classification-using-hg_api-epoch_2") model = AutoModelForSequenceClassification.from_pretrained("hyunkookim/roberta-base-klue-ynat-classification-using-hg_api-epoch_2") - Notebooks
- Google Colab
- Kaggle
File size: 971 Bytes
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"bos_token": {
"content": "[CLS]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"cls_token": {
"content": "[CLS]",
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"normalized": false,
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"single_word": false
},
"eos_token": {
"content": "[SEP]",
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},
"mask_token": {
"content": "[MASK]",
"lstrip": false,
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"rstrip": false,
"single_word": false
},
"pad_token": {
"content": "[PAD]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"sep_token": {
"content": "[SEP]",
"lstrip": false,
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"rstrip": false,
"single_word": false
},
"unk_token": {
"content": "[UNK]",
"lstrip": false,
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}
}
|