Instructions to use LikeWater2024/Buddhism-Llama3-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use LikeWater2024/Buddhism-Llama3-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf LikeWater2024/Buddhism-Llama3-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf LikeWater2024/Buddhism-Llama3-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf LikeWater2024/Buddhism-Llama3-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf LikeWater2024/Buddhism-Llama3-GGUF:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf LikeWater2024/Buddhism-Llama3-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf LikeWater2024/Buddhism-Llama3-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf LikeWater2024/Buddhism-Llama3-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf LikeWater2024/Buddhism-Llama3-GGUF:Q4_K_M
Use Docker
docker model run hf.co/LikeWater2024/Buddhism-Llama3-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use LikeWater2024/Buddhism-Llama3-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LikeWater2024/Buddhism-Llama3-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LikeWater2024/Buddhism-Llama3-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/LikeWater2024/Buddhism-Llama3-GGUF:Q4_K_M
- Ollama
How to use LikeWater2024/Buddhism-Llama3-GGUF with Ollama:
ollama run hf.co/LikeWater2024/Buddhism-Llama3-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use LikeWater2024/Buddhism-Llama3-GGUF with Docker Model Runner:
docker model run hf.co/LikeWater2024/Buddhism-Llama3-GGUF:Q4_K_M
- Lemonade
How to use LikeWater2024/Buddhism-Llama3-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull LikeWater2024/Buddhism-Llama3-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Buddhism-Llama3-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Buddhism Llama-3 GGUF (佛教禪宗大語言模型)
這是一個基於 Llama-3-8B-Instruct 微調的佛教禪宗模型,專注於解釋《金剛經》、《六祖壇經》等經典,並能以佛學視角回答現代問題。
模型介紹 (Model Introduction)
- 基礎模型: Unsloth Llama-3 8B Instruct
- 微調數據: 包含《金剛經》、《六祖壇經》及合成的佛學問答數據。
- 量化格式: GGUF (Q4_K_M)
使用方法 (Usage)
本模型為 GGUF 格式,可直接用於 Ollama 或 LM Studio。
Ollama 匯入指令:
- 下載
unsloth.Q4_K_M.gguf - 建立
Modelfile:
FROM ./unsloth.Q4_K_M.gguf
TEMPLATE """{{ if .System }}<|start_header_id|>system<|end_header_id|>
{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>
{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>
{{ .Response }}<|eot_id|>""" SYSTEM "你是一位精通佛法的高僧,請用慈悲與智慧的語氣,引用經典為眾生解惑。" PARAMETER stop "<|start_header_id|>" PARAMETER stop "<|end_header_id|>" PARAMETER stop "<|eot_id|>"
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Model tree for LikeWater2024/Buddhism-Llama3-GGUF
Base model
unsloth/llama-3-8b-Instruct