Update README.md

README.md

@@ -6,127 +6,16 @@ language:
 - en
 tags:
 - llama-cpp
+base_model:
+- elyza/Llama-3-ELYZA-JP-8B
 ---
 
-# Llama-3-ELYZA-JP-8B-GGUF
-
-![Llama-3-ELYZA-JP-8B-image](./key_visual.png)
+# Llama-3-shindy-jp-8B-GGUF
 
 ## Model Description
 
-**Llama-3-ELYZA-JP-8B** is a large language model trained by [ELYZA, Inc](https://elyza.ai/).
-Based on [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct), it has been enhanced for Japanese usage through additional pre-training and instruction tuning. (Built with Meta Llama3)
-
-For more details, please refer to [our blog post](https://note.com/elyza/n/n360b6084fdbd).
-
-## 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).
-
-The following table shows the performance degradation due to quantization:
-
-| Model | ELYZA-tasks-100 GPT4 score |
-| :-------------------------------- | ---: |
-| [Llama-3-ELYZA-JP-8B](https://huggingface.co/elyza/Llama-3-ELYZA-JP-8B)               | 3.655 |
-| [Llama-3-ELYZA-JP-8B-GGUF (Q4_K_M)](https://huggingface.co/elyza/Llama-3-ELYZA-JP-8B-GGUF) | 3.57  |
-| [Llama-3-ELYZA-JP-8B-AWQ](https://huggingface.co/elyza/Llama-3-ELYZA-JP-8B-AWQ)           | 3.39  |
-
-
-## Use with llama.cpp
-
-Install llama.cpp through brew (works on Mac and Linux):
-```bash
-brew install llama.cpp
-```
-
-Invoke the llama.cpp server:
-```bash
-$ llama-server \
---hf-repo elyza/Llama-3-ELYZA-JP-8B-GGUF \
---hf-file Llama-3-ELYZA-JP-8B-q4_k_m.gguf \
---port 8080
-```
-
-Call the API using curl:
-```bash
-$ curl http://localhost:8080/v1/chat/completions \
--H "Content-Type: application/json" \
--d '{
-  "messages": [
-    { "role": "system", "content": "あなたは誠実で優秀な日本人のアシスタントです。特に指示が無い場合は、常に日本語で回答してください。" },
-    { "role": "user", "content": "古代ギリシャを学ぶ上で知っておくべきポイントは？" }
-  ],
-  "temperature": 0.6,
-  "max_tokens": -1,
-  "stream": false
-}'
-```
-
-Call the API using Python:
-```python
-import openai
-
-client = openai.OpenAI(
-    base_url="http://localhost:8080/v1",
-    api_key = "dummy_api_key"
-)
-
-completion = client.chat.completions.create(
-    model="dummy_model_name",
-    messages=[
-        {"role": "system", "content": "あなたは誠実で優秀な日本人のアシスタントです。特に指示が無い場合は、常に日本語で回答してください。"},
-        {"role": "user", "content": "古代ギリシャを学ぶ上で知っておくべきポイントは？"}
-    ]
-)
-```
-
-## Use with Desktop App
-
-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](https://lmstudio.ai/).
-
-- **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. 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 an 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.
-
-![lmstudio-demo](./lmstudio-demo.gif)
-
-This demo showcases Llama-3-ELYZA-JP-8B-GGUF running smoothly on a MacBook Pro (M1 Pro), achieving an inference speed of approximately 20 tokens per second.
-
-## Developers
-
-Listed in alphabetical order.
-
-- [Masato Hirakawa](https://huggingface.co/m-hirakawa)
-- [Shintaro Horie](https://huggingface.co/e-mon)
-- [Tomoaki Nakamura](https://huggingface.co/tyoyo)
-- [Daisuke Oba](https://huggingface.co/daisuk30ba)
-- [Sam Passaglia](https://huggingface.co/passaglia)
-- [Akira Sasaki](https://huggingface.co/akirasasaki)
+Based on [elyza/Llama-3-ELYZA-JP-8B-GGUF](https://huggingface.co/elyza/Llama-3-ELYZA-JP-8B-GGUF), it has been enhanced for Japanese usage through additional pre-training and instruction tuning. (Built with Meta Llama3)
 
 ## License
 
-[Meta Llama 3 Community License](https://llama.meta.com/llama3/license/)
-
-## How to Cite
-
-```tex
-@misc{elyzallama2024,
-      title={elyza/Llama-3-ELYZA-JP-8B},
-      url={https://huggingface.co/elyza/Llama-3-ELYZA-JP-8B},
-      author={Masato Hirakawa and Shintaro Horie and Tomoaki Nakamura and Daisuke Oba and Sam Passaglia and Akira Sasaki},
-      year={2024},
-}
-```
-
-## Citations
-
-```tex
-@article{llama3modelcard,
-    title={Llama 3 Model Card},
-    author={AI@Meta},
-    year={2024},
-    url = {https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md}
-}
-```
+[Meta Llama 3 Community License](https://llama.meta.com/llama3/license/)