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README.md

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 - **Version:** 1.0
 - **Model Developers:** Neural Magic
 
-Quantized version of [Mistral-7B-Instruct-v0.3](mistralai/Mistral-7B-Instruct-v0.3).
+Quantized version of [Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3).
 It achieves an average score of 65.85 on the [OpenLLM](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) benchmark (version 1), whereas the unquantized model achieves 66.33.
 
 ### Model Optimizations
 
-This model was obtained by quantizing the weights and activations of [Mistral-7B-Instruct-v0.3](mistralai/Mistral-7B-Instruct-v0.3) to FP8 data type, ready for inference with vLLM >= 0.5.0.
+This model was obtained by quantizing the weights and activations of [Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) to FP8 data type, ready for inference with vLLM >= 0.5.0.
 This optimization reduces the number of bits per parameter from 16 to 8, reducing the disk size and GPU memory requirements by approximately 50%.
 
 Only the weights and activations of the linear operators within transformers blocks are quantized. Symmetric per-channel quantization is applied, in which a linear scaling per output dimension maps the FP8 representations of the quantized weights and activations.