Instructions to use MOllYeasy/R1MusicPos 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 MOllYeasy/R1MusicPos 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 MOllYeasy/R1MusicPos:Q4_K_M # Run inference directly in the terminal: llama cli -hf MOllYeasy/R1MusicPos:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf MOllYeasy/R1MusicPos:Q4_K_M # Run inference directly in the terminal: llama cli -hf MOllYeasy/R1MusicPos: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 MOllYeasy/R1MusicPos:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf MOllYeasy/R1MusicPos: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 MOllYeasy/R1MusicPos:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf MOllYeasy/R1MusicPos:Q4_K_M
Use Docker
docker model run hf.co/MOllYeasy/R1MusicPos:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use MOllYeasy/R1MusicPos with Ollama:
ollama run hf.co/MOllYeasy/R1MusicPos:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use MOllYeasy/R1MusicPos with Docker Model Runner:
docker model run hf.co/MOllYeasy/R1MusicPos:Q4_K_M
- Lemonade
How to use MOllYeasy/R1MusicPos with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull MOllYeasy/R1MusicPos:Q4_K_M
Run and chat with the model
lemonade run user.R1MusicPos-Q4_K_M
List all available models
lemonade list
- Atomic Chat
音乐情感交互实验模型 (Music-Positive / 积极组)
这是论文研究中使用的实验模型:积极共情组。 该模型基于 DeepSeek-R1 构建,旨在模拟一位温暖、专业且具有高度共情能力 的音乐知音。
实验用途
用于探究在实验的人机交互设计中“积极共情的人机交互”是否能提升被试对AI音乐表演的接受度。
如何运行 (使用 Ollama)
- 确保已安装 Ollama。
- 在终端运行以下命令即可直接拉取并运行:
ollama run hf.co/MOLLyeasy/DeepSeek-R1-Music-Positive
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