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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7414e4fd8ab0867c3d5305889f04d42bb43f2a1a521e51b5d543b79ef2786e15
- Size of remote file:
- 134 MB
- SHA256:
- 83633d479343283e882eaa496024877e75404207c2ee9ae12847c5d344fa4f20
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