Instructions to use PavanDeepak/Topic_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PavanDeepak/Topic_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PavanDeepak/Topic_Classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PavanDeepak/Topic_Classification") model = AutoModelForSequenceClassification.from_pretrained("PavanDeepak/Topic_Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from PavanDeepak/Topic_Classification: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
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https://huggingface.co/PavanDeepak/Topic_Classification/resolve/0f5f83eaaadc4a13af6c892ac6ffe63382470cbb/tokenizer.json
- Command line
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hf download hf://PavanDeepak/Topic_Classification@0f5f83eaaadc4a13af6c892ac6ffe63382470cbb/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/PavanDeepak/Topic_Classification/resolve/0f5f83eaaadc4a13af6c892ac6ffe63382470cbb/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.