https://github.com/cookyman74/study_lanchain

https://github.com/cookyman74/study_lanchain

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• Host: GitHub
• URL: https://github.com/cookyman74/study_lanchain
• Owner: cookyman74
• Created: 2024-04-24T15:54:58.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2024-05-31T13:36:41.000Z (8 months ago)
• Last Synced: 2024-05-31T19:01:23.902Z (8 months ago)
• Language: Jupyter Notebook
• Size: 5.4 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# study_lanchain

## 설치 및 테스트 방법

`Hugging Face와 ollama를 통해 설치 방법은 다음과 같다.`

### 1. gguf 모델 다운로드 

[gguf 모델 다운로드](https://huggingface.co/QuantFactory/Meta-Llama-3-8B-Instruct-GGUF/tree/main)

* Meta-Llama-3-8B-Instruct.Q5_1.gguf

### 2. Modelfile 생성

```

FROM Meta-Llama-3-8B-Instruct.Q8_0.gguf

TEMPLATE """{{- if .System }}

<|begin_of_text|>system {{ .System }}<|end_of_text|>

{{- end }}

<|begin_of_text|>user

{{ .Prompt }}<|end_of_text|>

<|begin_of_text|>assistant

"""

SYSTEM """A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions."""

PARAMETER temperature 0

PARAMETER num_ctx 4096

PARAMETER stop <|begin_of_text|>

PARAMETER stop <|end_of_text|>

PARAMETER stop <|eot_id|>

PARAMETER stop <|end_of_text|>

```

### 3. Ollama 모델 생성 및 확인

```bash

ollama create llama3-instruct-8b -f Modelfile

ollama list

```

### 4. Ollama 실행

```

ollama run llama3-instruct-8b

```

* 설치 사용 리뷰 

일단 한글은 파인튜닝되지 않아, 정확하지 않았으나,

영어로 물어본 것에 대해서는 8B 모델이라도 매우 훌륭하다. (php오류를 찾아 물어봤더니 굉장히 정확히 찾았다)

### 5. Ollama WebUI 설치 방법

Assuming you already have Docker and Ollama running on your computer, installation is super simple.

```bash

docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main

```

The simply go to http://localhost:3000, make an account, and start chatting away!