Update README.md

README.md

@@ -15,7 +15,7 @@ license: llama2
 Dromedary-2 is an open-source self-aligned language model trained in minimal human supervision with the SALMON (Self-Alignment with Principle-Following Reward Models) technique.
 The base language model is LLaMA-70b, based on the transformer architecture.
 
-**NOTE: *Dromedary-2* is trained with QLoRA and the bfloat16 data type.** While it is [possible](https://gist.github.com/ChrisHayduk/1a53463331f52dca205e55982baf9930) to merge the QLoRA weights with the quantized model and thus enable inference with libraries such as [TGI](https://github.com/huggingface/text-generation-inference) and [vLLM](https://github.com/vllm-project/vllm), we found the merged weights can lead to degenerated performance. Therefore, we recommend directly loading the QLoRA weights with the PEFT-LoRA framework.
+**NOTE: *Dromedary-2* is trained with [QLoRA](https://github.com/artidoro/qlora) and the bfloat16 data type.** While it is [possible](https://gist.github.com/ChrisHayduk/1a53463331f52dca205e55982baf9930) to merge the QLoRA weights with the quantized model and thus enable inference with libraries such as [TGI](https://github.com/huggingface/text-generation-inference) and [vLLM](https://github.com/vllm-project/vllm), we found the merged weights can lead to degenerated performance. Therefore, we recommend directly loading the QLoRA weights with the [PEFT-LoRA](https://github.com/huggingface/peft) framework.
 
 Please check the [inference section](https://github.com/IBM/SALMON/inference) of our repo for the complete inference code.