Instructions to use akoksal/bounti with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akoksal/bounti with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="akoksal/bounti")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("akoksal/bounti") model = AutoModelForSequenceClassification.from_pretrained("akoksal/bounti") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f1fe087739ab8c40857388ebced3d9eafa0abd1020ccb89f097567e32d925a3
- Size of remote file:
- 737 MB
- SHA256:
- 70580bbb52046595770047ad3c82b051f8ef03dd112422038d0ddf71adde7ded
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