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:
- ac121bb97f1547cfaf17e89c8ff5b21b5278736d5e2f9005b3d7d8d62fe65923
- Size of remote file:
- 954 kB
- SHA256:
- 23a9dfdefd63d9113c174efbef90270882d228ef0ce97f92d672d6eeefb7b251
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