Zero-Shot Classification
Transformers
PyTorch
TensorFlow
Safetensors
xlm-roberta
text-classification
tensorflow
nli
natural-language-inference
Eval Results (legacy)
Instructions to use nahiar/zero-shot-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nahiar/zero-shot-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="nahiar/zero-shot-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nahiar/zero-shot-classification") model = AutoModelForSequenceClassification.from_pretrained("nahiar/zero-shot-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitattributes from nahiar/zero-shot-classification: direct link, hf CLI and curl.
- Browser
- Download file 459 Bytes
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https://huggingface.co/nahiar/zero-shot-classification/resolve/main/.gitattributes
- Command line
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hf download hf://nahiar/zero-shot-classification/.gitattributes
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curl -L -o .gitattributes https://huggingface.co/nahiar/zero-shot-classification/resolve/main/.gitattributes
459 Bytes
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