Instructions to use baseten/gemma-4-e2b-it-sequence-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use baseten/gemma-4-e2b-it-sequence-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="baseten/gemma-4-e2b-it-sequence-classification", trust_remote_code=True)# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("baseten/gemma-4-e2b-it-sequence-classification", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("baseten/gemma-4-e2b-it-sequence-classification", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +0 -4
config.json
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},
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"image_token_id": 258880,
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"initializer_range": 0.02,
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"label2id": {
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"no": 0,
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"yes": 1
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},
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"model_type": "gemma4",
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"pad_token_id": 0,
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"problem_type": "single_label_classification",
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},
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"image_token_id": 258880,
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"initializer_range": 0.02,
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"model_type": "gemma4",
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"pad_token_id": 0,
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"problem_type": "single_label_classification",
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