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README.md

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 ## Model Details
 
-Today (September 17th, 2024), we introduce [NVLM 1.0](https://arxiv.org/abs/2409.11402), a family of frontier-class multimodal large language models (LLMs) that achieve state-of-the-art results on vision-language tasks, rivaling the leading proprietary models (e.g., GPT-4o) and open-access models (e.g., Llama 3-V 405B and InternVL 2). Remarkably, NVLM 1.0 shows improved text-only performance over its LLM backbone after multimodal training. We are open-sourcing the model weights and code for the community.
+Today (September 17th, 2024), we introduce [NVLM 1.0](https://arxiv.org/abs/2409.11402), a family of frontier-class multimodal large language models (LLMs) that achieve state-of-the-art results on vision-language tasks, rivaling the leading proprietary models (e.g., GPT-4o) and open-access models (e.g., Llama 3-V 405B and InternVL 2). Remarkably, NVLM 1.0 shows improved text-only performance over its LLM backbone after multimodal training. 
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+In this repo, we are open-sourcing NVLM-1.0-D-72B (decoder-only architecture), the decoder-only model weights and code for the community.
 
 ## Other Resources
-[Inference Code (HF)](https://huggingface.co/nvidia/NVLM-1.0-D-72B/tree/main)   [Training Code (Coming soon)]()   [Website](https://nvlm-project.github.io/)   [Paper](https://arxiv.org/abs/2409.11402)
+[Inference Code (HF)](https://huggingface.co/nvidia/NVLM-D-72B/tree/main)   [Training Code (Coming soon)]()   [Website](https://nvlm-project.github.io/)   [Paper](https://arxiv.org/abs/2409.11402)
 
 ## Benchmark Results
 We train our model with legacy [Megatron-LM](https://github.com/NVIDIA/Megatron-LM/tree/main/megatron/legacy) and adapt the codebase to Huggingface for model hosting, reproducibility, and inference.