Instructions to use gghfez/MiMo-V2.5-ikllama-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 gghfez/MiMo-V2.5-ikllama-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 gghfez/MiMo-V2.5-ikllama-GGUF:IQ3_S # Run inference directly in the terminal: llama cli -hf gghfez/MiMo-V2.5-ikllama-GGUF:IQ3_S
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf gghfez/MiMo-V2.5-ikllama-GGUF:IQ3_S # Run inference directly in the terminal: llama cli -hf gghfez/MiMo-V2.5-ikllama-GGUF:IQ3_S
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 gghfez/MiMo-V2.5-ikllama-GGUF:IQ3_S # Run inference directly in the terminal: ./build/bin/llama cli -hf gghfez/MiMo-V2.5-ikllama-GGUF:IQ3_S
Use Docker
docker model run hf.co/gghfez/MiMo-V2.5-ikllama-GGUF:IQ3_S
- Llama new
- LM Studio
- Jan
- Ollama
How to use gghfez/MiMo-V2.5-ikllama-GGUF with Ollama:
ollama run hf.co/gghfez/MiMo-V2.5-ikllama-GGUF:IQ3_S
- Unsloth Desktop
- Pi
How to use gghfez/MiMo-V2.5-ikllama-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf gghfez/MiMo-V2.5-ikllama-GGUF:IQ3_S
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "gghfez/MiMo-V2.5-ikllama-GGUF:IQ3_S" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use gghfez/MiMo-V2.5-ikllama-GGUF with Docker Model Runner:
docker model run hf.co/gghfez/MiMo-V2.5-ikllama-GGUF:IQ3_S
- Lemonade
How to use gghfez/MiMo-V2.5-ikllama-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull gghfez/MiMo-V2.5-ikllama-GGUF:IQ3_S
Run and chat with the model
lemonade run user.MiMo-V2.5-ikllama-GGUF-IQ3_S
List all available models
lemonade list
- Hermes Agent
How to use gghfez/MiMo-V2.5-ikllama-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf gghfez/MiMo-V2.5-ikllama-GGUF:IQ3_S
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default gghfez/MiMo-V2.5-ikllama-GGUF:IQ3_S
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use gghfez/MiMo-V2.5-ikllama-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf gghfez/MiMo-V2.5-ikllama-GGUF:IQ3_S
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "gghfez/MiMo-V2.5-ikllama-GGUF:IQ3_S" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Model
This is a text-only GGUF quantization of XiaomiMiMo/MiMo-V2.5 with unfused atten q,k,v for compatibility with ik_llama.cpp
Re-uploaded from AesSedai/MiMo-V2.5-GGUF prior to this change
Available quants: IQ4_XS and IQ3_S
From AesSedai's model card:
| Quant | Size | Mixture | PPL | 1-(Mean PPL(Q)/PPL(base)) | KLD |
|---|---|---|---|---|---|
| Q8_0 | 306.66 GiB (8.50 BPW) | Unknown / TBD | 5.134769 ยฑ 0.030261 | +0.1230% | 0.012010 ยฑ 0.000150 |
| Q5_K_M | 213.39 GiB (5.92 BPW) | Q8_0 / Q5_K / Q5_K / Q6_K | 5.147654 ยฑ 0.030377 | +0.3743% | 0.014752 ยฑ 0.000240 |
| Q4_K_M | 177.68 GiB (4.93 BPW) | Q8_0 / Q4_K / Q4_K / Q5_K | 5.202785 ยฑ 0.030828 | +1.4493% | 0.020631 ยฑ 0.000251 |
| IQ4_XS | 137.75 GiB (3.82 BPW) | Q8_0 / IQ3_S / IQ3_S / IQ4_XS | 5.272594 ยฑ 0.031193 | +2.8105% | 0.041508 ยฑ 0.000343 |
| IQ3_S | 106.31 GiB (2.95 BPW) | Q6_K / IQ2_S / IQ2_S / IQ3_S | 5.545001 ยฑ 0.033188 | +8.1221% | 0.092415 ยฑ 0.000600 |
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