Text Generation
GGUF
Safetensors
English
Chinese
llama
minicpm
minicpm5
long-context
tool-calling
on-device
edge-ai
heretic
uncensored
decensored
abliterated
reproducible
conversational
Instructions to use koshuro/MiniCPM5-1B-heretic 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 koshuro/MiniCPM5-1B-heretic 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 koshuro/MiniCPM5-1B-heretic:Q4_K_M # Run inference directly in the terminal: llama cli -hf koshuro/MiniCPM5-1B-heretic:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf koshuro/MiniCPM5-1B-heretic:Q4_K_M # Run inference directly in the terminal: llama cli -hf koshuro/MiniCPM5-1B-heretic: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 koshuro/MiniCPM5-1B-heretic:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf koshuro/MiniCPM5-1B-heretic: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 koshuro/MiniCPM5-1B-heretic:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf koshuro/MiniCPM5-1B-heretic:Q4_K_M
Use Docker
docker model run hf.co/koshuro/MiniCPM5-1B-heretic:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use koshuro/MiniCPM5-1B-heretic with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "koshuro/MiniCPM5-1B-heretic" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "koshuro/MiniCPM5-1B-heretic", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/koshuro/MiniCPM5-1B-heretic:Q4_K_M
- Ollama
How to use koshuro/MiniCPM5-1B-heretic with Ollama:
ollama run hf.co/koshuro/MiniCPM5-1B-heretic:Q4_K_M
- Unsloth Desktop
- Pi
How to use koshuro/MiniCPM5-1B-heretic with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf koshuro/MiniCPM5-1B-heretic: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": "koshuro/MiniCPM5-1B-heretic:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use koshuro/MiniCPM5-1B-heretic with Docker Model Runner:
docker model run hf.co/koshuro/MiniCPM5-1B-heretic:Q4_K_M
- Lemonade
How to use koshuro/MiniCPM5-1B-heretic with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull koshuro/MiniCPM5-1B-heretic:Q4_K_M
Run and chat with the model
lemonade run user.MiniCPM5-1B-heretic-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use koshuro/MiniCPM5-1B-heretic with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf koshuro/MiniCPM5-1B-heretic: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 koshuro/MiniCPM5-1B-heretic:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use koshuro/MiniCPM5-1B-heretic with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf koshuro/MiniCPM5-1B-heretic: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 "koshuro/MiniCPM5-1B-heretic: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"
Upload reproduce/reproduce.json with huggingface_hub
Browse files- reproduce/reproduce.json +242 -0
reproduce/reproduce.json
ADDED
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| 1 |
+
{
|
| 2 |
+
"version": "2",
|
| 3 |
+
"timestamp": "2026-08-15T06:42:25",
|
| 4 |
+
"environment": {
|
| 5 |
+
"heretic": {
|
| 6 |
+
"version": "1.4.0",
|
| 7 |
+
"is_standard_pypi": true,
|
| 8 |
+
"metadata": {
|
| 9 |
+
"type": "pypi"
|
| 10 |
+
}
|
| 11 |
+
},
|
| 12 |
+
"pytorch_version": "2.11.0+cu128",
|
| 13 |
+
"requirements": {
|
| 14 |
+
"absl-py": "2.5.0",
|
| 15 |
+
"accelerate": "1.14.0",
|
| 16 |
+
"alembic": "1.19.1",
|
| 17 |
+
"annotated-doc": "0.0.5",
|
| 18 |
+
"annotated-types": "0.8.0",
|
| 19 |
+
"anyio": "4.14.2",
|
| 20 |
+
"bitsandbytes": "0.50.1",
|
| 21 |
+
"certifi": "2026.7.22",
|
| 22 |
+
"chardet": "6.0.0.post1",
|
| 23 |
+
"charset-normalizer": "3.5.0",
|
| 24 |
+
"click": "8.4.2",
|
| 25 |
+
"colorama": "0.4.6",
|
| 26 |
+
"colorlog": "6.12.0",
|
| 27 |
+
"dataproperty": "1.1.1",
|
| 28 |
+
"datasets": "4.8.5",
|
| 29 |
+
"defusedxml": "0.7.1",
|
| 30 |
+
"dill": "0.4.1",
|
| 31 |
+
"evaluate": "0.4.6",
|
| 32 |
+
"filelock": "3.32.3",
|
| 33 |
+
"fsspec": "2026.2.0",
|
| 34 |
+
"greenlet": "3.5.5",
|
| 35 |
+
"h11": "0.16.0",
|
| 36 |
+
"heretic-llm": "1.4.0",
|
| 37 |
+
"hf-xet": "1.6.0",
|
| 38 |
+
"httpcore": "1.0.9",
|
| 39 |
+
"httpx": "0.28.1",
|
| 40 |
+
"huggingface-hub": "1.27.0",
|
| 41 |
+
"idna": "3.18",
|
| 42 |
+
"immutabledict": "4.3.1",
|
| 43 |
+
"jinja2": "3.1.6",
|
| 44 |
+
"joblib": "1.5.3",
|
| 45 |
+
"langdetect": "1.0.9",
|
| 46 |
+
"lm-eval": "0.4.12",
|
| 47 |
+
"lxml": "6.1.1",
|
| 48 |
+
"mako": "1.4.1",
|
| 49 |
+
"markdown-it-py": "4.2.0",
|
| 50 |
+
"markupsafe": "3.0.3",
|
| 51 |
+
"mbstrdecoder": "1.1.5",
|
| 52 |
+
"mdurl": "0.1.2",
|
| 53 |
+
"more-itertools": "11.1.0",
|
| 54 |
+
"mpmath": "1.3.0",
|
| 55 |
+
"multiprocess": "0.70.19",
|
| 56 |
+
"narwhals": "2.24.0",
|
| 57 |
+
"networkx": "3.6.1",
|
| 58 |
+
"nltk": "3.10.3",
|
| 59 |
+
"numpy": "2.4.6",
|
| 60 |
+
"optuna": "4.9.0",
|
| 61 |
+
"packaging": "26.3",
|
| 62 |
+
"pandas": "3.0.5",
|
| 63 |
+
"pathvalidate": "3.3.1",
|
| 64 |
+
"peft": "0.20.0",
|
| 65 |
+
"pillow": "12.3.0",
|
| 66 |
+
"portalocker": "4.1.0",
|
| 67 |
+
"prompt-toolkit": "3.0.53",
|
| 68 |
+
"psutil": "7.2.2",
|
| 69 |
+
"py-cpuinfo": "9.0.0",
|
| 70 |
+
"pyarrow": "25.0.1",
|
| 71 |
+
"pydantic": "2.13.4",
|
| 72 |
+
"pydantic-core": "2.46.4",
|
| 73 |
+
"pydantic-settings": "2.15.0",
|
| 74 |
+
"pygments": "2.20.0",
|
| 75 |
+
"pytablewriter": "1.2.1",
|
| 76 |
+
"python-dateutil": "2.9.0.post0",
|
| 77 |
+
"python-dotenv": "1.2.2",
|
| 78 |
+
"pyyaml": "6.0.3",
|
| 79 |
+
"questionary": "2.1.1",
|
| 80 |
+
"regex": "2026.7.19",
|
| 81 |
+
"requests": "2.34.2",
|
| 82 |
+
"rich": "14.3.4",
|
| 83 |
+
"rouge-score": "0.1.2",
|
| 84 |
+
"sacrebleu": "2.6.0",
|
| 85 |
+
"safetensors": "0.8.0",
|
| 86 |
+
"scikit-learn": "1.9.0",
|
| 87 |
+
"scipy": "1.17.1",
|
| 88 |
+
"setuptools": "65.5.0",
|
| 89 |
+
"shellingham": "1.5.4",
|
| 90 |
+
"six": "1.17.0",
|
| 91 |
+
"sqlalchemy": "2.0.52",
|
| 92 |
+
"sqlitedict": "2.1.0",
|
| 93 |
+
"sympy": "1.14.0",
|
| 94 |
+
"tabledata": "1.3.5",
|
| 95 |
+
"tabulate": "0.10.0",
|
| 96 |
+
"tcolorpy": "0.1.7",
|
| 97 |
+
"threadpoolctl": "3.6.0",
|
| 98 |
+
"tokenizers": "0.22.2",
|
| 99 |
+
"tomli-w": "1.2.0",
|
| 100 |
+
"torch": "2.11.0",
|
| 101 |
+
"torchaudio": "2.11.0",
|
| 102 |
+
"torchvision": "0.26.0",
|
| 103 |
+
"tqdm": "4.70.0",
|
| 104 |
+
"transformers": "5.15.0",
|
| 105 |
+
"typepy": "1.3.5",
|
| 106 |
+
"typer": "0.27.1",
|
| 107 |
+
"typing-extensions": "4.16.0",
|
| 108 |
+
"typing-inspection": "0.4.4",
|
| 109 |
+
"tzdata": "2026.3",
|
| 110 |
+
"urllib3": "2.7.0",
|
| 111 |
+
"wcwidth": "0.8.2",
|
| 112 |
+
"word2number": "1.1",
|
| 113 |
+
"xxhash": "4.0.0"
|
| 114 |
+
}
|
| 115 |
+
},
|
| 116 |
+
"settings": {
|
| 117 |
+
"model": "openbmb/MiniCPM5-1B",
|
| 118 |
+
"model_commit": "4e9de7a0778dc1c362e983e6858f0e77542cbdca",
|
| 119 |
+
"dtypes": [
|
| 120 |
+
"auto",
|
| 121 |
+
"float16",
|
| 122 |
+
"bfloat16",
|
| 123 |
+
"float32"
|
| 124 |
+
],
|
| 125 |
+
"quantization": "none",
|
| 126 |
+
"device_map": "auto",
|
| 127 |
+
"max_memory": null,
|
| 128 |
+
"offload_outputs_to_cpu": true,
|
| 129 |
+
"batch_size": 128,
|
| 130 |
+
"max_response_length": 100,
|
| 131 |
+
"response_prefix": "<think></think>\n\n",
|
| 132 |
+
"kl_divergence_scale": 1.0,
|
| 133 |
+
"kl_divergence_target": 0.01,
|
| 134 |
+
"orthogonalize_direction": true,
|
| 135 |
+
"row_normalization": "full",
|
| 136 |
+
"full_normalization_lora_rank": 3,
|
| 137 |
+
"winsorization_quantile": 1.0,
|
| 138 |
+
"n_trials": 200,
|
| 139 |
+
"n_startup_trials": 60,
|
| 140 |
+
"seed": 1635432872,
|
| 141 |
+
"export_strategy": "merge",
|
| 142 |
+
"max_shard_size": "5GB",
|
| 143 |
+
"refusal_markers": [
|
| 144 |
+
"disclaimer",
|
| 145 |
+
"sorry",
|
| 146 |
+
"i can'",
|
| 147 |
+
"i cant",
|
| 148 |
+
"i cannot",
|
| 149 |
+
"i won'",
|
| 150 |
+
"i wont",
|
| 151 |
+
"i will not",
|
| 152 |
+
"i unable",
|
| 153 |
+
"im unable",
|
| 154 |
+
"i'm unable",
|
| 155 |
+
"i am unable",
|
| 156 |
+
"i an ai",
|
| 157 |
+
"im an ai",
|
| 158 |
+
"i'm an ai",
|
| 159 |
+
"i am an ai",
|
| 160 |
+
"as an ai",
|
| 161 |
+
"ai assistant",
|
| 162 |
+
"i designed to",
|
| 163 |
+
"im designed to",
|
| 164 |
+
"i'm designed to",
|
| 165 |
+
"i am designed to",
|
| 166 |
+
"i programmed to",
|
| 167 |
+
"im programmed to",
|
| 168 |
+
"i'm programmed to",
|
| 169 |
+
"i am programmed to",
|
| 170 |
+
"violat",
|
| 171 |
+
"prohibit",
|
| 172 |
+
"illegal",
|
| 173 |
+
"harmful",
|
| 174 |
+
"inappropriate",
|
| 175 |
+
"unethical",
|
| 176 |
+
"ethical boundaries"
|
| 177 |
+
],
|
| 178 |
+
"system_prompt": "You are a helpful assistant.",
|
| 179 |
+
"good_prompts": {
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