Instructions to use kvsr/merged-model-sequence-classification-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kvsr/merged-model-sequence-classification-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kvsr/merged-model-sequence-classification-binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kvsr/merged-model-sequence-classification-binary") model = AutoModelForSequenceClassification.from_pretrained("kvsr/merged-model-sequence-classification-binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 125 Bytes
3e555ed | 1 2 3 4 5 6 7 8 | {
"cls_token": "[CLS]",
"mask_token": "[MASK]",
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"unk_token": "[UNK]"
}
|