Instructions to use sparsh35/trained_gemma_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sparsh35/trained_gemma_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sparsh35/trained_gemma_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sparsh35/trained_gemma_classifier") model = AutoModelForSequenceClassification.from_pretrained("sparsh35/trained_gemma_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
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