EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Hacker News·Aug 3·5 min read
Explanation of INT8 ConvRot (FP8 is no longer needed)
TL;DR
INT8 ConvRot, a new quantization method supported in ComfyUI v0.27.0, outperforms FP8 formats on GeForce RTX 20/30 and 40/50 series. It is set to become the standard for 8-bit quantized models.
✦ Why It Matters
Adopt INT8 ConvRot in your projects to enhance performance on supported NVIDIA GPUs today.
Key Takeaways
- Implement INT8 ConvRot in your AI models for better performance.
- Update to ComfyUI v0.27.0 to access INT8 ConvRot support.
- Test model performance on RTX 20/30 series for optimal results.
- Consider converting existing models to INT8 ConvRot for efficiency.
How It Works
INT8 ConvRot employs a combination of convolution and rotation techniques to distribute outliers across multiple dimensions. This innovative approach allows integer-based models to handle a wider range of values, thus improving accuracy and performance compared to traditional methods.