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:
- 5de28ef25fcca586ca6e84108ca9818b4eda3f872a18396ea95bfb81b0fbbf19
- Size of remote file:
- 2.29 kB
- SHA256:
- c515f1b7f43f48fe573e48a20074f459ac5f46a3a1f387473d84893e166dc3fb
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