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)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("GautamR/kmai_gte_base_classifier", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ed31b659327eca50d70d58532a7fea0dee8e4cba01def6d7d3be492d1b7d3a3
- Size of remote file:
- 550 MB
- SHA256:
- c3a7d6998dd607a45aa7c5e97dda0ab8a9026cda1f81586e2efb9fcd61ee62b2
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