Instructions to use ioxdue/moediet-runs 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 ioxdue/moediet-runs 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 ioxdue/moediet-runs:Q4_K_M # Run inference directly in the terminal: llama cli -hf ioxdue/moediet-runs:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ioxdue/moediet-runs:Q4_K_M # Run inference directly in the terminal: llama cli -hf ioxdue/moediet-runs:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf ioxdue/moediet-runs:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf ioxdue/moediet-runs:Q4_K_M
Use Docker
docker model run hf.co/ioxdue/moediet-runs:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use ioxdue/moediet-runs with Ollama:
ollama run hf.co/ioxdue/moediet-runs:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use ioxdue/moediet-runs with Docker Model Runner:
docker model run hf.co/ioxdue/moediet-runs:Q4_K_M
- Lemonade
How to use ioxdue/moediet-runs with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ioxdue/moediet-runs:Q4_K_M
Run and chat with the model
lemonade run user.moediet-runs-Q4_K_M
List all available models
lemonade list
- Atomic Chat
MoEDiet run artifacts
Run outputs of MoEDiet experiments: audited
expert-pruning checkpoints, quantized GGUF exports, masks, and build reports, organized
per job under runs/<JOB_ID>/ (source snapshots of each submitted job are kept under
requests/<ID>/).
Weights are derivatives of Apache-2.0 models (AllenAI OLMoE-1B-7B-0125-Instruct,
Qwen/Qwen3-Next-80B-A3B-Instruct) and are distributed under the same Apache-2.0 terms,
with attribution to the original authors. Each run directory carries its own
report.json with the exact source revision, routing, and quality audit.
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Hardware compatibility
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