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NVLM-D-72B

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@@ -19,7 +19,7 @@ Today (September 17th, 2024), we introduce [NVLM 1.0](https://arxiv.org/abs/2409
 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-D-72B/tree/main) &ensp; [Training Code (Coming soon)]() &ensp; [Website](https://nvlm-project.github.io/) &ensp; [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.

 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-D-72B/tree/main) &ensp; [Training Code (Coming soon)]() &ensp; [Website](https://research.nvidia.com/labs/adlr/NVLM-1/) &ensp; [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.