Instructions to use Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf", filename="Mistral-Small-4-119B-2603-heretic-i1-IQ2_S.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Rioky/Mistral-Small-4-119B-2603-heretic-i1-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 Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf Rioky/Mistral-Small-4-119B-2603-heretic-i1-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 Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf Rioky/Mistral-Small-4-119B-2603-heretic-i1-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 Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Rioky/Mistral-Small-4-119B-2603-heretic-i1-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 Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf:Q4_K_M
Use Docker
docker model run hf.co/Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Rioky/Mistral-Small-4-119B-2603-heretic-i1-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": "Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf:Q4_K_M
- Ollama
How to use Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf with Ollama:
ollama run hf.co/Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf:Q4_K_M
- Unsloth Studio
How to use Rioky/Mistral-Small-4-119B-2603-heretic-i1-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 Rioky/Mistral-Small-4-119B-2603-heretic-i1-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 Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf to start chatting
- Pi
How to use Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf:Q4_K_M
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": "Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Rioky/Mistral-Small-4-119B-2603-heretic-i1-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 Rioky/Mistral-Small-4-119B-2603-heretic-i1-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 Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Rioky/Mistral-Small-4-119B-2603-heretic-i1-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 "Rioky/Mistral-Small-4-119B-2603-heretic-i1-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"
- Docker Model Runner
How to use Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf with Docker Model Runner:
docker model run hf.co/Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf:Q4_K_M
- Lemonade
How to use Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Rioky/Mistral-Small-4-119B-2603-heretic-i1-gguf:Q4_K_M
Run and chat with the model
lemonade run user.Mistral-Small-4-119B-2603-heretic-i1-gguf-Q4_K_M
List all available models
lemonade list
Mistral-Small-4-119B-2603-heretic GGUf Quantizations (imatrix)
Model Information
| Field | Value |
|---|---|
| Base Model | Mistral Small 4 119B 2603 by Mistralai |
| Heretic Model | Mistral Small 4 119B 2603 Heretic by darkc0de |
| Architecture | Mistral4 (MoE, MLA attention) |
| Total Parameters | 119B |
| Active Parameters | 6.5B per token |
| Experts | 128 experts, 4 active |
| Context Length | 256k tokens |
Key Features
- MoE Architecture: 128 experts with 4 active per token (6.5B activated parameters)
- Multimodal: Accepts both text and image input, produces text output
- Reasoning Mode: Toggle between fast instant reply and reasoning mode with test-time compute
- Function Calling: Native function calling with JSON output
- Agentic: Best-in-class agentic capabilities
- System Prompts: Strong adherence and support for system prompts
- Speed-Optimized: Best-in-class performance and speed
- Large Context Window: 256k context length supported
- Apache 2.0 License: Open-source for commercial and non-commercial use
- Multilingual: Supports English, French, Spanish, German, Italian, Portuguese, Dutch, Chinese, Japanese, Korean, Arabic and more
Heretic Model Statistics
| Metric | Value |
|---|---|
| KL Divergence | 0.0167 (0 for refusable tokens by definition) |
| Refusals | 27/100 (98/100 original model) |
imatrix Quantizations
These models were quantized using an importance matrix (imatrix) computed from a reference corpus. The imatrix helps preserve quality for important token patterns, typically yielding better results at low bitrates compared to standard quantization.
The imatrix file was generated using the Q8_0 quantization of the heretic model on the following calibration dataset:
Calibration Dataset: bartowski1182/calibration_datav5.txt Reference imatrix: Mistral-Small-4-119B-2603-heretic-imatrix.gguf (118 MB)
Available Quantizations
| File | Type | Size | BPW | Description |
|---|---|---|---|---|
Mistral-Small-4-119B-2603-heretic-i1-Q6_K.gguf |
Q6_K | 91.0 GiB | 6.00 | High quality |
Mistral-Small-4-119B-2603-heretic-i1-Q5_K_M.gguf |
Q5_K_M | 78.5 GiB | 5.37 | Recommended |
Mistral-Small-4-119B-2603-heretic-i1-Q4_K_M.gguf |
Q4_K_M | 67.2 GiB | 4.58 | |
Mistral-Small-4-119B-2603-heretic-i1-IQ4_NL.gguf |
IQ4_NL | 62.5 GiB | 4.50 | Non-linear quantization |
Mistral-Small-4-119B-2603-heretic-i1-Q3_K_L.gguf |
Q3_K_L | 57.4 GiB | 3.70 | |
Mistral-Small-4-119B-2603-heretic-i1-Q3_K_M.gguf |
Q3_K_M | 53.1 GiB | 3.63 | |
Mistral-Small-4-119B-2603-heretic-i1-Q3_K_S.gguf |
Q3_K_S | 47.8 GiB | 3.41 | |
Mistral-Small-4-119B-2603-heretic-i1-IQ4_XS.gguf |
IQ4_XS | 59.1 GiB | 4.25 | Linear variant |
Mistral-Small-4-119B-2603-heretic-i1-Q2_K.gguf |
Q2_K | 40.4 GiB | 2.96 | |
Mistral-Small-4-119B-2603-heretic-i1-IQ3_XS.gguf |
IQ3_XS | 45.3 GiB | 3.30 | |
Mistral-Small-4-119B-2603-heretic-i1-IQ3_XXS.gguf |
IQ3_XXS | 42.7 GiB | 3.06 | |
Mistral-Small-4-119B-2603-heretic-i1-IQ2_S.gguf |
IQ2_S | 32.8 GiB | 2.50 | |
Mistral-Small-4-119B-2603-heretic-i1-IQ2_XS.gguf |
IQ2_XS | 32.4 GiB | 2.34 | |
Mistral-Small-4-119B-2603-heretic-i1-IQ2_XXS.gguf |
IQ2_XXS | 29.0 GiB | 2.10 | Lowest memory usage |
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Base model
mistralai/Mistral-Small-4-119B-2603