Update README.md

README.md

@@ -20,9 +20,10 @@ Based on [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama
 For more details, please refer to [our blog post](https://note.com/elyza/n/n360b6084fdbd).
 
 ## Quantization
-We performed quantization using [llama.cpp](https://github.com/ggerganov/llama.cpp) and converted the model to GGUF format. Currently, we only offer quantized models in the Q4_K_M format.
 
-We have prepared two quantized model options, GGUF and AWQ. Here is the table measuring the performance degradation due to quantization.
+We have prepared two quantized model options, GGUF and AWQ. This is the GGUF (Q4_K_M) model, converted using [llama.cpp](https://github.com/ggerganov/llama.cpp).
+
+Here is a table showing the performance degradation due to quantization.
 
 | Model | ELYZA-tasks-100 GPT4 score |
 | :-------------------------------- | ---: |
@@ -37,6 +38,7 @@ Install llama.cpp through brew (works on Mac and Linux)
 ```bash
 brew install llama.cpp
 ```
+
 Invoke the llama.cpp server.
 
 ```bash
@@ -83,17 +85,13 @@ completion = client.chat.completions.create(
 
 ## Use with Desktop App
 
-There are various desktop applications that can handle GGUF models, but here we will introduce how to use a model in a local environment without coding by using LM Studio.
+There are various desktop applications that can handle GGUF models, but here we will introduce how to use the model in the no-code environment LM Studio.
 
 - **Installation**: Download and install [LM Studio](https://lmstudio.ai/).
 - **Downloading the Model**: Search for `elyza/Llama-3-ELYZA-JP-8B-GGUF` in the search bar on the home page 🏠, and download `Llama-3-ELYZA-JP-8B-q4_k_m.gguf`.
-- **Start Chatting**: Click on 💬 in the sidebar, select `Llama-3-ELYZA-JP-8B-GGUF` from "Select a Model to load" in the header, and load the model. Now you can freely chat with the local LLM.
-- **Setting Options**: You can set options from the sidebar on the right. Faster inference can be achieved by setting Quick GPU Offload Settings to Max in the GPU Settings.
-- **For Developers, Starting the API Server**: Click `<->` in the left sidebar and move to the Local Server tab. Select the model and click Start Server to launch an OpenAI API-compatible API server.
-
-## Quantization Options
-
-Currently, we only offer quantized models in the Q4_K_M format.
+- **Start Chatting**: Click on 💬 in the sidebar, select `Llama-3-ELYZA-JP-8B-GGUF` from "Select a Model to load" in the header, and load the model. You can now freely chat with the local LLM.
+- **Setting Options**: You can set options from the sidebar on the right. Faster inference can be achieved by setting Quick GPU Offload to Max in the GPU Settings.
+- **For Developers: Starting the API Server**: Click `<->` in the left sidebar and move to the Local Server tab. Select the model and click Start Server to launch an OpenAI API-compatible API server.
 
 ## Developers