Instructions to use bumblebee-testing/tiny-random-Gemma3TextForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bumblebee-testing/tiny-random-Gemma3TextForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bumblebee-testing/tiny-random-Gemma3TextForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bumblebee-testing/tiny-random-Gemma3TextForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("bumblebee-testing/tiny-random-Gemma3TextForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c87e1256d661a994858fe4dc0c97690a4e3723059799c4db7f933d1b187e8a7
- Size of remote file:
- 954 kB
- SHA256:
- 6db34a9f20c1708f0a5b0ab85742a7ab85d6c1aee6fe824488597ec24c35e2f7
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