feat: Add native Gemma3 support for ONNX export#92
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- Add Gemma3OnnxConfig class with proper configuration - Register gemma3 model type for text generation and classification tasks - Add Gemma3 to supported architectures and test mappings - Set minimum transformers version requirement to 4.50.0 - Follow same pattern as existing Gemma/Gemma2 implementations Fixes: ValueError when exporting Gemma3 models to ONNX format Resolves: 'gemma3 model, that is a custom or unsupported architecture' error
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I don't think this does much at the moment. |
Author
Yup, it doesn't. Will see what happens in the progress. |
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Add Gemma3 VLM Support for ONNX Export
🎯 Overview
This PR adds comprehensive support for Gemma3 Vision Language Model (VLM) variants in the ONNX export functionality, enabling users to export both Gemma2 base models and PaliGemma VLM models to ONNX format.
1. Gemma2 Base Model Support
gemma2models.gemma2.Gemma2OnnxConfigdefault- Basic inferencedefault-with-past- Optimized inference with KV cachecausal-lm- Causal language modelingcausal-lm-with-past- Optimized causal LM with KV cachesequence-classification- Text classificationtoken-classification- Token-level classification2. PaliGemma VLM Support
paligemmamodels.paligemma.PaliGemmaOnnxConfigdefault- Basic inferencevision2seq-lm- Vision-to-sequence language modeling