Text Classification
Transformers
PyTorch
Safetensors
deberta-v2
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use w11wo/deberta-v3-base-isarcasm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use w11wo/deberta-v3-base-isarcasm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="w11wo/deberta-v3-base-isarcasm")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("w11wo/deberta-v3-base-isarcasm") model = AutoModelForSequenceClassification.from_pretrained("w11wo/deberta-v3-base-isarcasm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc78a399aa0bf32b87f5316d9f559ff9b4fb7e2df8b5c956b1c36603cd7eabeb
- Size of remote file:
- 4.54 kB
- SHA256:
- 5bcbc89969360b6c481daaf9e9605c59a559fad797729898b35ee820d1437aa9
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