Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use heavyhelium/deberta-v3-base-touche-enhanced-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-enhanced-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-enhanced-binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("heavyhelium/deberta-v3-base-touche-enhanced-binary") model = AutoModelForSequenceClassification.from_pretrained("heavyhelium/deberta-v3-base-touche-enhanced-binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 38e7513656799a89bc5134d7c6e063b231ec3cd265898ba9c825f0f99af17bf5
- Size of remote file:
- 5.46 kB
- SHA256:
- 93f806474ebe5496f38d70c1271ce311df22cd265567c6605d78ff19cd04c25a
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