Instructions to use saidutta69/MiniCPM5-2B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use saidutta69/MiniCPM5-2B-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 saidutta69/MiniCPM5-2B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf saidutta69/MiniCPM5-2B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf saidutta69/MiniCPM5-2B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf saidutta69/MiniCPM5-2B-GGUF: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 saidutta69/MiniCPM5-2B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf saidutta69/MiniCPM5-2B-GGUF: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 saidutta69/MiniCPM5-2B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf saidutta69/MiniCPM5-2B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/saidutta69/MiniCPM5-2B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use saidutta69/MiniCPM5-2B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "saidutta69/MiniCPM5-2B-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "saidutta69/MiniCPM5-2B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/saidutta69/MiniCPM5-2B-GGUF:Q4_K_M

Ollama
How to use saidutta69/MiniCPM5-2B-GGUF with Ollama:
```
ollama run hf.co/saidutta69/MiniCPM5-2B-GGUF:Q4_K_M
```
Unsloth Desktop

How to use saidutta69/MiniCPM5-2B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf saidutta69/MiniCPM5-2B-GGUF:Q4_K_M

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": "saidutta69/MiniCPM5-2B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use saidutta69/MiniCPM5-2B-GGUF with Docker Model Runner:
```
docker model run hf.co/saidutta69/MiniCPM5-2B-GGUF:Q4_K_M
```

Lemonade

How to use saidutta69/MiniCPM5-2B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull saidutta69/MiniCPM5-2B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.MiniCPM5-2B-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use saidutta69/MiniCPM5-2B-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 saidutta69/MiniCPM5-2B-GGUF:Q4_K_M

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 saidutta69/MiniCPM5-2B-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use saidutta69/MiniCPM5-2B-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf saidutta69/MiniCPM5-2B-GGUF:Q4_K_M

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 "saidutta69/MiniCPM5-2B-GGUF:Q4_K_M" \
  --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"

MiniCPM5-2B GGUF (imatrix-calibrated)

GGUF conversions of openbmb/MiniCPM5-2B with importance-matrix calibration, so the K-quants and i-quants keep more quality at small sizes than uncalibrated equivalents.

Pipeline: convert_hf_to_gguf.py --outtype f16 with latest llama.cpp, then llama-imatrix over 100 chunks of WikiText-2 train (ctx 512), then llama-quantize --imatrix for the calibrated types. The exact matrix used is included as MiniCPM5-2B.imatrix, and every file below carries a measured perplexity (WikiText-2 test subset, 200KB, ctx 512, llama-perplexity on CPU).

Files

File	Quant	Size	Calibrated	PPL	vs F16
`MiniCPM5-2B-Q8_0.gguf`	Q8_0	~2.4 GB	-	15.18	+0.02
`MiniCPM5-2B-Q6_K.gguf`	Q6_K	~2.0 GB	-	15.24	+0.08
`MiniCPM5-2B-Q5_K_M.gguf`	Q5_K_M	~1.7 GB	yes	15.39	+0.23
`MiniCPM5-2B-Q4_K_M.gguf`	Q4_K_M	~1.5 GB	yes	15.65	+0.49
`MiniCPM5-2B-IQ4_XS.gguf`	IQ4_XS	~1.4 GB	yes	15.88	+0.72
`MiniCPM5-2B.imatrix`	-	3 MB	-	-	-

F16 reference PPL: 15.16.

Pick Q4_K_M for the best size/quality trade-off (+0.49 PPL at 1.5 GB), IQ4_XS for the smallest usable file (+0.72 at 1.4 GB), Q8_0 for near-lossless (+0.02).

Usage

# llama.cpp
./llama-cli -m MiniCPM5-2B-Q4_K_M.gguf -p "Explain quantization in one sentence."

# Ollama
ollama create minicpm5-2b -f - <<EOF
FROM ./MiniCPM5-2B-Q4_K_M.gguf
EOF
ollama run minicpm5-2b

Downloads last month: 191

GGUF

Model size

3B params

Architecture

llama

Hardware compatibility

4-bit

5-bit

6-bit

8-bit

Model tree for saidutta69/MiniCPM5-2B-GGUF

Base model

openbmb/MiniCPM5-2B

Quantized

(83)

this model