Instructions to use Atharva192003/zero-shot-classfier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Atharva192003/zero-shot-classfier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="Atharva192003/zero-shot-classfier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Atharva192003/zero-shot-classfier") model = AutoModelForSequenceClassification.from_pretrained("Atharva192003/zero-shot-classfier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Atharva192003/zero-shot-classfier: direct link, hf CLI and curl.
- Browser
- Download file 1.36 MB
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https://huggingface.co/Atharva192003/zero-shot-classfier/resolve/main/tokenizer.json
- Command line
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hf download hf://Atharva192003/zero-shot-classfier/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Atharva192003/zero-shot-classfier/resolve/main/tokenizer.json
1.36 MB
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