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  # Instella-VL-1B ✨
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  Welcome to the official repository for **Instella-VL-1B**, AMD's first ever Vision-Language Model (VLM). This repository provides a detailed guide for training and inference with **Instella-VL-1B**. Developed from AMD's **Instella-1B** (previously known as [AMD OLMo 1B SFT](https://www.amd.com/en/developer/resources/technical-articles/introducing-the-first-amd-1b-language-model.html) LLM), this model is fully open-source, with both model weights and training code available for AMD GPUs (MI300). Its compact size aims to make it accessible to a broad spectrum of researchers, developers, and enthusiasts, enabling them to build upon, modify, and integrate it into their own projects.
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- [[GitHub](https://github.com/AMD-AIG-AIMA/InstellaVL)][[Blog](https://github.com/AMD-AIG-AIMA/Instella-VL/blog/blog-final.md)]
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  ## Main Results
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  We compare our model with models which only releases the model weights (with * in the below table) and also models which releases weights, data curvation and all training details.
 
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  # Instella-VL-1B ✨
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  Welcome to the official repository for **Instella-VL-1B**, AMD's first ever Vision-Language Model (VLM). This repository provides a detailed guide for training and inference with **Instella-VL-1B**. Developed from AMD's **Instella-1B** (previously known as [AMD OLMo 1B SFT](https://www.amd.com/en/developer/resources/technical-articles/introducing-the-first-amd-1b-language-model.html) LLM), this model is fully open-source, with both model weights and training code available for AMD GPUs (MI300). Its compact size aims to make it accessible to a broad spectrum of researchers, developers, and enthusiasts, enabling them to build upon, modify, and integrate it into their own projects.
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+ [[GitHub](https://github.com/AMD-AIG-AIMA/InstellaVL)][[Blog](https://rocm.blogs.amd.com/artificial-intelligence/Instella-BL-1B-VLM/README.html)]
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  ## Main Results
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  We compare our model with models which only releases the model weights (with * in the below table) and also models which releases weights, data curvation and all training details.