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:
- f1962dfaff2adc78e9942b5ed0e6bd89329af628be3d0564214feced7011d6ea
- Size of remote file:
- 738 MB
- SHA256:
- a34afaaafdde143dd514d5baa9ec0672f67c5008128b5f6b5fa58f02cc2d612c
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