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