Instructions to use gghfez/MiMo-V2.5-ikllama-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use gghfez/MiMo-V2.5-ikllama-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="gghfez/MiMo-V2.5-ikllama-GGUF",
	filename="MiMo-V2.5-IQ3_S-00001-of-00004.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use gghfez/MiMo-V2.5-ikllama-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -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-server -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

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 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/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 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

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 Studio

How to use gghfez/MiMo-V2.5-ikllama-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for gghfez/MiMo-V2.5-ikllama-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for gghfez/MiMo-V2.5-ikllama-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for gghfez/MiMo-V2.5-ikllama-GGUF to start chatting

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-server -hf gghfez/MiMo-V2.5-ikllama-GGUF:IQ3_S

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/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

Hermes Agent new

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-server -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

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

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 ± 0.030261	+0.1230%	0.012010 ± 0.000150
Q5_K_M	213.39 GiB (5.92 BPW)	Q8_0 / Q5_K / Q5_K / Q6_K	5.147654 ± 0.030377	+0.3743%	0.014752 ± 0.000240
Q4_K_M	177.68 GiB (4.93 BPW)	Q8_0 / Q4_K / Q4_K / Q5_K	5.202785 ± 0.030828	+1.4493%	0.020631 ± 0.000251
IQ4_XS	137.75 GiB (3.82 BPW)	Q8_0 / IQ3_S / IQ3_S / IQ4_XS	5.272594 ± 0.031193	+2.8105%	0.041508 ± 0.000343
IQ3_S	106.31 GiB (2.95 BPW)	Q6_K / IQ2_S / IQ2_S / IQ3_S	5.545001 ± 0.033188	+8.1221%	0.092415 ± 0.000600

Downloads last month: 1,004

GGUF

Model size

309B params

Architecture

mimo2

Hardware compatibility

3-bit

4-bit

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Model tree for gghfez/MiMo-V2.5-ikllama-GGUF

Base model

XiaomiMiMo/MiMo-V2.5

Quantized

(21)

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