Instructions to use syedkhalid0/DeBERTa-Zero-Shot-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syedkhalid0/DeBERTa-Zero-Shot-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="syedkhalid0/DeBERTa-Zero-Shot-Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("syedkhalid0/DeBERTa-Zero-Shot-Classification") model = AutoModelForSequenceClassification.from_pretrained("syedkhalid0/DeBERTa-Zero-Shot-Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 464b197d36ac192c99ab18f17fd6141944954c5ca986c6c8151fc03e48d46374
- Size of remote file:
- 369 MB
- SHA256:
- 2a2d9e8fc302d1a04f0325c4b0d37aa504f64971667078ad04dfbb7120006d2f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.