Instructions to use praxis-app/praxis-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use praxis-app/praxis-models 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 praxis-app/praxis-models:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf praxis-app/praxis-models:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf praxis-app/praxis-models:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf praxis-app/praxis-models: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 praxis-app/praxis-models:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf praxis-app/praxis-models: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 praxis-app/praxis-models:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf praxis-app/praxis-models:Q4_K_M

Use Docker

docker model run hf.co/praxis-app/praxis-models:Q4_K_M

LM Studio
Jan
Ollama
How to use praxis-app/praxis-models with Ollama:
```
ollama run hf.co/praxis-app/praxis-models:Q4_K_M
```

Unsloth Studio

How to use praxis-app/praxis-models 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 praxis-app/praxis-models 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 praxis-app/praxis-models to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for praxis-app/praxis-models to start chatting

How to use praxis-app/praxis-models with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf praxis-app/praxis-models: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": "praxis-app/praxis-models:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use praxis-app/praxis-models with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf praxis-app/praxis-models: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 "praxis-app/praxis-models: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 praxis-app/praxis-models with Docker Model Runner:
```
docker model run hf.co/praxis-app/praxis-models:Q4_K_M
```

Lemonade

How to use praxis-app/praxis-models with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull praxis-app/praxis-models:Q4_K_M

Run and chat with the model

lemonade run user.praxis-models-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use praxis-app/praxis-models with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf praxis-app/praxis-models: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 praxis-app/praxis-models:Q4_K_M

Run Hermes

hermes

Atomic Chat

praxis-models

Commit History

Add Qwen3-4B Q4_K_M GGUF (byte-for-byte from unsloth/Qwen3-4B-GGUF)

00206fe
verified

hooliganbeer commited on 14 days ago

Remove Qwen2.5-3B (superseded by Qwen3-4B per selection update)

4caabe0
verified

hooliganbeer commited on 14 days ago

Add Qwen2.5-3B-Instruct Q4_K_M GGUF (byte-for-byte from Qwen/Qwen2.5-3B-Instruct-GGUF)

7dccf60
verified

hooliganbeer commited on 14 days ago

Add Qwen3-ASR-0.6B int8 ONNX (byte-for-byte from modelscope zengshuishui/Qwen3-ASR-onnx)

e1ae5a1
verified

hooliganbeer commited on 14 days ago

Add SaT sat-12l-sm mixed-io32 ONNX (desktop-exported, int8 emb + fp16 transformer + fp32 I/O) + XLM-R spm

991ab6f
verified

hooliganbeer commited on 14 days ago

Add Qwen3-1.7B Q4_K_M GGUF (byte-for-byte redistribution of unsloth's quantization)

29579d0
verified

hooliganbeer commited on 15 days ago

Add SenseVoice int8 (byte-for-byte redistribution of upstream 2024-07-17 export)

307c8bf
verified

hooliganbeer commited on 15 days ago

initial commit

a1a2b78
verified

hooliganbeer commited on 15 days ago

Commit History

Add Qwen3-4B Q4_K_M GGUF (byte-for-byte from unsloth/Qwen3-4B-GGUF) 00206fe verified

Remove Qwen2.5-3B (superseded by Qwen3-4B per selection update) 4caabe0 verified

Add Qwen2.5-3B-Instruct Q4_K_M GGUF (byte-for-byte from Qwen/Qwen2.5-3B-Instruct-GGUF) 7dccf60 verified

Add Qwen3-ASR-0.6B int8 ONNX (byte-for-byte from modelscope zengshuishui/Qwen3-ASR-onnx) e1ae5a1 verified

Add SaT sat-12l-sm mixed-io32 ONNX (desktop-exported, int8 emb + fp16 transformer + fp32 I/O) + XLM-R spm 991ab6f verified

Add Qwen3-1.7B Q4_K_M GGUF (byte-for-byte redistribution of unsloth's quantization) 29579d0 verified

Add SenseVoice int8 (byte-for-byte redistribution of upstream 2024-07-17 export) 307c8bf verified

initial commit a1a2b78 verified

Add Qwen3-4B Q4_K_M GGUF (byte-for-byte from unsloth/Qwen3-4B-GGUF)

00206fe
verified

Remove Qwen2.5-3B (superseded by Qwen3-4B per selection update)

4caabe0
verified

Add Qwen2.5-3B-Instruct Q4_K_M GGUF (byte-for-byte from Qwen/Qwen2.5-3B-Instruct-GGUF)

7dccf60
verified

Add Qwen3-ASR-0.6B int8 ONNX (byte-for-byte from modelscope zengshuishui/Qwen3-ASR-onnx)

e1ae5a1
verified

Add SaT sat-12l-sm mixed-io32 ONNX (desktop-exported, int8 emb + fp16 transformer + fp32 I/O) + XLM-R spm

991ab6f
verified

Add Qwen3-1.7B Q4_K_M GGUF (byte-for-byte redistribution of unsloth's quantization)

29579d0
verified

Add SenseVoice int8 (byte-for-byte redistribution of upstream 2024-07-17 export)

307c8bf
verified

initial commit

a1a2b78
verified