EleutherAI/the_pile_deduplicated
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How to use hell0ks/MiMo-V2.5-GGUF-ko with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="hell0ks/MiMo-V2.5-GGUF-ko", filename="imatrix.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
How to use hell0ks/MiMo-V2.5-GGUF-ko with llama.cpp:
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf hell0ks/MiMo-V2.5-GGUF-ko:IQ3_S # Run inference directly in the terminal: llama-cli -hf hell0ks/MiMo-V2.5-GGUF-ko:IQ3_S
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf hell0ks/MiMo-V2.5-GGUF-ko:IQ3_S # Run inference directly in the terminal: llama-cli -hf hell0ks/MiMo-V2.5-GGUF-ko:IQ3_S
# 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 hell0ks/MiMo-V2.5-GGUF-ko:IQ3_S # Run inference directly in the terminal: ./llama-cli -hf hell0ks/MiMo-V2.5-GGUF-ko:IQ3_S
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 hell0ks/MiMo-V2.5-GGUF-ko:IQ3_S # Run inference directly in the terminal: ./build/bin/llama-cli -hf hell0ks/MiMo-V2.5-GGUF-ko:IQ3_S
docker model run hf.co/hell0ks/MiMo-V2.5-GGUF-ko:IQ3_S
How to use hell0ks/MiMo-V2.5-GGUF-ko with Ollama:
ollama run hf.co/hell0ks/MiMo-V2.5-GGUF-ko:IQ3_S
How to use hell0ks/MiMo-V2.5-GGUF-ko with Unsloth Studio:
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 hell0ks/MiMo-V2.5-GGUF-ko to start chatting
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 hell0ks/MiMo-V2.5-GGUF-ko to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for hell0ks/MiMo-V2.5-GGUF-ko to start chatting
How to use hell0ks/MiMo-V2.5-GGUF-ko with Pi:
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf hell0ks/MiMo-V2.5-GGUF-ko:IQ3_S
# 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": "hell0ks/MiMo-V2.5-GGUF-ko:IQ3_S"
}
]
}
}
}# Start Pi in your project directory: pi
How to use hell0ks/MiMo-V2.5-GGUF-ko with Hermes Agent:
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf hell0ks/MiMo-V2.5-GGUF-ko:IQ3_S
# 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 hell0ks/MiMo-V2.5-GGUF-ko:IQ3_S
hermes
How to use hell0ks/MiMo-V2.5-GGUF-ko with Docker Model Runner:
docker model run hf.co/hell0ks/MiMo-V2.5-GGUF-ko:IQ3_S
How to use hell0ks/MiMo-V2.5-GGUF-ko with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull hell0ks/MiMo-V2.5-GGUF-ko:IQ3_S
lemonade run user.MiMo-V2.5-GGUF-ko-IQ3_S
lemonade list
llm.create_chat_completion(
messages = "No input example has been defined for this model task."
)This is basically same as AesSedai/MiMo-V2.5-GGUF, but with Korean-focused imatrix dataset.
| Dataset | Language | Type | Topic | Comment |
|---|---|---|---|---|
| EleutherAI/the_pile_deduplicated | English | text | English corpus | 15%, 16384 |
| KORMo-Team/Cosmopedia-ko-synth | Korean | text | Korean corpus | 35%, 8192 |
| Korean chat generated with Gemma 4 | Korean | messages | Korean chat | 35%, 8192 |
| SWE-bench/SWE-smith-trajectories | English | messages | Tool calling | 15%, 8192 |
Create imatrix using llama-imatrix with --parse-special flag
Followed AesSedai's quantize method
export TYPE_FFN_UP_EXPS=IQ2_S
export TYPE_FFN_GATE_EXPS=IQ2_S
export TYPE_FFN_DOWN_EXPS=IQ3_S
export TYPE_DEFAULT=Q6_K
llama-quantize \
--allow-requantize \
--tensor-type ffn_up_exps=$TYPE_FFN_UP_EXPS \
--tensor-type ffn_gate_exps=$TYPE_FFN_GATE_EXPS \
--tensor-type ffn_down_exps=$TYPE_FFN_DOWN_EXPS \
--imatrix $imatrix $gguf_path $TYPE_DEFAULT
Special thanks to AesSedai for implementing MiMo support for llama.cpp and quantize method.
3-bit
Base model
XiaomiMiMo/MiMo-V2.5
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="hell0ks/MiMo-V2.5-GGUF-ko", filename="", )