Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use heavyhelium/deberta-v3-base-touche-base-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use heavyhelium/deberta-v3-base-touche-base-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="heavyhelium/deberta-v3-base-touche-base-binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("heavyhelium/deberta-v3-base-touche-base-binary") model = AutoModelForSequenceClassification.from_pretrained("heavyhelium/deberta-v3-base-touche-base-binary") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3a617ba7310f7020ada4788238d585ff881faa5a727ab4d452e6d7625ba4a6f
- Size of remote file:
- 738 MB
- SHA256:
- f0a0a1d281aab0a461823e963aadacc9a65dc68eb988dec097f8bd720ca006ee
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