Text Classification
Transformers
TensorFlow
deberta-v2
generated_from_keras_callback
text-embeddings-inference
Instructions to use sanagnos/deberta-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sanagnos/deberta-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sanagnos/deberta-v3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sanagnos/deberta-v3") model = AutoModelForSequenceClassification.from_pretrained("sanagnos/deberta-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e40fe3373ed6842ae830613dd3b7c9bfbadaa502314fcc37a3022b4ba9b108d
- Size of remote file:
- 1.74 GB
- SHA256:
- 336663b0e76cd793e8bdb3f73f05d1d11a3bc080ab0855fabb7db2d5c8b8e9ee
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