Update README.md

README.md

@@ -13,9 +13,7 @@ We extend the context length of Llama-3-8B-Instruct to 80K using QLoRA and 3.5K
 
 **NOTE**: This repo contains the quantized model of [namespace-Pt/Llama-3-8B-Instruct-80K-QLoRA-Merged](https://huggingface.co/namespace-Pt/Llama-3-8B-Instruct-80K-QLoRA-Merged). The quantization is conducted with [llama.cpp](https://github.com/ggerganov/llama.cpp) (Q4_K_M and Q8_0).
 
-All the following evaluation results are based on the [UNQUANTIZED MODEL](https://huggingface.co/namespace-Pt/Llama-3-8B-Instruct-80K-QLoRA-Merged). They can be reproduced following instructions [here](https://github.com/FlagOpen/FlagEmbedding/tree/master/Long_LLM/longllm_qlora). 
-
-**NOTE**: After quantization, you may observe quality degradation.
+All the following evaluation results are based on the [UNQUANTIZED MODEL](https://huggingface.co/namespace-Pt/Llama-3-8B-Instruct-80K-QLoRA-Merged). They can be reproduced following instructions [here](https://github.com/FlagOpen/FlagEmbedding/tree/master/Long_LLM/longllm_qlora). However, after quantization, you may observe **quality degradation**.
 
 ## Needle in a Haystack
 We evaluate the model on the Needle-In-A-HayStack task using the official setting. The blue vertical line indicates the training context length, i.e. 80K.