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 ## News
-* 12/23/2024 [1.5.0](https://github.com/ModelCloud/GPTQModel/releases/tag/v1.5.0): Multi-modal (image-to-text) optimized quantization support added for Qwen 2-VL and Ovis 1.6-VL. Previously image-to-text model quantization was not using image calibration data and post-quant result was less than optimal. 1.5.0 is the first release to release a stable path for multi-modal quantization: note only text layers are quantized.  
+* 12/23/2024 [1.5.0](https://github.com/ModelCloud/GPTQModel/releases/tag/v1.5.0): Multi-modal (image-to-text) optimized quantization support has been added for Qwen 2-VL and Ovis 1.6-VL. Previous image-to-text model quantizations did not use image calibration data, resulting in less than optimal post-quantization results. Version 1.5.0 is the first release to provide a stable path for multi-modal quantization: only text layers are quantized.
 * 12/19/2024 [1.4.5](https://github.com/ModelCloud/GPTQModel/releases/tag/v1.4.5): Windows 11 support added/validated. Ovis VL model support with image dataset calibration. Fixed `dynamic` loading. Reduced quantization vram usage. 
 * 12/15/2024 [1.4.2](https://github.com/ModelCloud/GPTQModel/releases/tag/v1.4.2): MacOS `gpu` (Metal) and `cpu` (M+) support added/validated for inference and quantization. Cohere 2 model support added. 
 * 12/13/2024 [1.4.1](https://github.com/ModelCloud/GPTQModel/releases/tag/v1.4.1): Added Qwen2-VL model support. `mse` quantization control exposed in `QuantizeConfig`. Monkey patch `patch_vllm()` and `patch_hf()` api added to allow Transformers/Optimum/PEFT and vLLM to correctly loaded GPTQModel quantized models while upstream PRs are in pending status.