Instructions to use GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-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 GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-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 GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-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 GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-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 GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-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 GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF:Q4_K_M

Use Docker

docker model run hf.co/GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-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": "GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF:Q4_K_M

Ollama
How to use GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF with Ollama:
```
ollama run hf.co/GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF:Q4_K_M
```
Unsloth Desktop

How to use GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-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": "GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF with Docker Model Runner:
```
docker model run hf.co/GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF:Q4_K_M
```

Lemonade

How to use GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-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 GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-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 GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-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 "GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-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-Claude-Fable5-1-Thinking-Agentic-GGUF

GGUF quantizations of MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic for llama.cpp, Ollama, LM Studio, jan, KoboldCpp, and other GGUF runtimes.

This repository provides local-deployment builds of a 2B Thinking model fine-tuned on Claude data atop openbmb/MiniCPM5-2B, with a strong focus on agentic tool calling, coding, and instruction following. MiniCPM5's native chat template is embedded in the GGUF files.

Transformers checkpoint: MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic

Files

File	Quant	Size	Notes
`MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-F16.gguf`	F16	~4.7 GB	full-precision conversion base
`MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-Q8_0.gguf`	Q8_0	~2.5 GB	recommended default
`MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-Q4_K_M.gguf`	Q4_K_M	~1.5 GB	smallest, for memory-constrained devices

Q8_0 is the recommended default quant for this 2B model. Q4_K_M is available for ultra-lightweight deployment.

Quick start

llama.cpp (`llama-cli`)

llama-cli \
  -m MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-Q8_0.gguf \
  -p "Write a Python function to merge two sorted lists." \
  -n 512 \
  --temp 1.0 --top-p 0.95 --min-p 0.0 \
  -c 8192

The model supports up to 128K tokens (131,072) per config.json. Set -c according to your available VRAM/RAM.

llama.cpp server

llama-server \
  -m MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-Q8_0.gguf \
  -c 8192 --port 8080

LM Studio / jan / KoboldCpp

Load any .gguf file from this repository. The MiniCPM5 chat template is embedded in the GGUF metadata.

Sampling recommendations

Inherited from openbmb/MiniCPM5-2B:

Scenario	Params
Default	`temperature=1.0, top_p=0.95, min_p=0.0`
If repetitive outputs	`temperature=1.0, top_p=0.95, min_p=0.0, repetition_penalty=1.05`

This model is Thinking-only — chain-of-thought reasoning is always active.

Support for sampling parameters varies across inference frameworks — check your runtime's documentation.

Capabilities

Agentic tool calling — reliable function-calling / tool-use behavior designed for multi-step agentic workflows
Claude fine-tune — post-trained on Claude data
Coding — code generation, debugging, and software-engineering workflows
Instruction following — reliable adherence to user prompts and task constraints
Thinking mode — chain-of-thought reasoning; MiniCPM5 chat template baked into the GGUF
Long context — up to 128K tokens (131,072 tokens per upstream config.json)

Benchmark

Scores for the Transformers checkpoint MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic:

ClawBench (Agentic Coding)

Model	QwenClawBench	WildClawBench
MiniCPM5-2B	42.11	23.19
MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic	44.56 (+2.45)	24.32 (+1.13)

ClawBench evaluates agentic coding ability — the model's capacity to autonomously use tools, navigate codebases, and complete multi-step software engineering tasks.

More benchmarks (BFCL, SWE-bench, Tau-Bench, etc.) coming soon.

Limitations

Thinking outputs — the model may emit reasoning blocks before the final answer
2B scale — lightweight local deployment; not frontier-scale
Runtime context — actual usable context depends on your GGUF runtime and hardware limits

Provenance & licensing

Apache-2.0, inherited from MiniCPM5-2B.

Acknowledgements

Base model: OpenBMB / MiniCPM5-2B
Transformers checkpoint: MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic
Quantization: llama.cpp

Downloads last month: 6,201

GGUF

Model size

3B params

Architecture

llama

Hardware compatibility

4-bit

8-bit

16-bit

Model tree for GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF

Base model

openbmb/MiniCPM5-2B

Finetuned

GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic

Quantized

(3)

this model

GnLOLot
/

MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF

MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF

Files

Quick start

llama.cpp (`llama-cli`)

llama.cpp server

LM Studio / jan / KoboldCpp

Sampling recommendations

Capabilities

Benchmark

ClawBench (Agentic Coding)

Limitations

Provenance & licensing

Acknowledgements

Model tree for GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF

Space using GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF 1

MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF

Files

Quick start

llama.cpp (llama-cli)

llama.cpp server

LM Studio / jan / KoboldCpp

Sampling recommendations

Capabilities

Benchmark

ClawBench (Agentic Coding)

Limitations

Provenance & licensing

Acknowledgements

Model tree for GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF

Space using GnLOLot/MiniCPM5-2B-Claude-Fable5-1-Thinking-Agentic-GGUF 1

llama.cpp (`llama-cli`)