Instructions to use daxa-ai/pebblo-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use daxa-ai/pebblo-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="daxa-ai/pebblo-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("daxa-ai/pebblo-classifier") model = AutoModelForSequenceClassification.from_pretrained("daxa-ai/pebblo-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Model V9 Release (#12)
Verified signature- Update model to version 9: Improved performance metrics and evaluation results (5fbbe83dee7ef72c61a8173c4ccf27b19788fc2e) Co-authored-by: Harshit <Tihsrah-CD@users.noreply.huggingface.co>402f3c6
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Model V8 Release (#11)
Verified signature- Improved Model Performance in V8 (6ad7434acfaf9033dbff8ace1b863ba7f87101ec) Co-authored-by: Harshit <Tihsrah-CD@users.noreply.huggingface.co>8fbe0dc
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Custom inference code for SageMaker deployment (#9)
Verified signature- Custom inference code for aws (a211030719303b038c551e8378aeb0c21ea4c79f)8595e5b
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Update README with model card details (#5)
Verified signature- Updated README.md with Model Card (ebbece91a1dee4a2fbf8b5e4d1f3a9eee02c44ac) Co-authored-by: Harshit <Tihsrah-CD@users.noreply.huggingface.co>3afb3ae
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Update config.json with consistent label names (#4)
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adding models and label encoder
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