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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4da99fdf4c048ddc6e0422621fa2a106efb52403cca52cd297475a294dcfbc43
- Size of remote file:
- 738 MB
- SHA256:
- f4239c7fd50eb67e20df044a2e4e3c8a9ccc8430a2dd9e42e2d13b66c13bb5b2
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