Instructions to use lastbrowser/sidekick-cortex-pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lastbrowser/sidekick-cortex-pro with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lastbrowser/sidekick-cortex-pro", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use lastbrowser/sidekick-cortex-pro 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 lastbrowser/sidekick-cortex-pro:Q4_K_M # Run inference directly in the terminal: llama cli -hf lastbrowser/sidekick-cortex-pro:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf lastbrowser/sidekick-cortex-pro:Q4_K_M # Run inference directly in the terminal: llama cli -hf lastbrowser/sidekick-cortex-pro:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf lastbrowser/sidekick-cortex-pro:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf lastbrowser/sidekick-cortex-pro:Q4_K_M
Use Docker
docker model run hf.co/lastbrowser/sidekick-cortex-pro:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use lastbrowser/sidekick-cortex-pro with Ollama:
ollama run hf.co/lastbrowser/sidekick-cortex-pro:Q4_K_M
- Unsloth Desktop
- Pi
How to use lastbrowser/sidekick-cortex-pro with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf lastbrowser/sidekick-cortex-pro: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": "lastbrowser/sidekick-cortex-pro:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use lastbrowser/sidekick-cortex-pro with Docker Model Runner:
docker model run hf.co/lastbrowser/sidekick-cortex-pro:Q4_K_M
- Lemonade
How to use lastbrowser/sidekick-cortex-pro with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull lastbrowser/sidekick-cortex-pro:Q4_K_M
Run and chat with the model
lemonade run user.sidekick-cortex-pro-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use lastbrowser/sidekick-cortex-pro with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf lastbrowser/sidekick-cortex-pro: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 lastbrowser/sidekick-cortex-pro:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use lastbrowser/sidekick-cortex-pro with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf lastbrowser/sidekick-cortex-pro: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 "lastbrowser/sidekick-cortex-pro: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"
Download tests/run_benchmark.py from lastbrowser/sidekick-cortex-pro: direct link, hf CLI and curl.
- Browser
- Download file 2.06 kB
-
https://huggingface.co/lastbrowser/sidekick-cortex-pro/resolve/main/tests/run_benchmark.py
- Command line
-
hf download hf://lastbrowser/sidekick-cortex-pro/tests/run_benchmark.py
-
curl -L -o run_benchmark.py https://huggingface.co/lastbrowser/sidekick-cortex-pro/resolve/main/tests/run_benchmark.py
2.06 kB
| #!/usr/bin/env python3 | |
| """Independent Sidekick Cortex Pro (formerly Axon) benchmark runner. | |
| Uses Ollama /api/chat with the dataset's persona system message (temp 0). | |
| Usage: | |
| python tests/run_benchmark.py lastbrowser/sidekick-cortex-pro:latest \\ | |
| data/axon_handwritten_testset_50.jsonl outputs_hw50.jsonl | |
| python tests/score.py outputs_hw50.jsonl | |
| """ | |
| import json, time, sys, requests | |
| def main(): | |
| if len(sys.argv) < 4: | |
| print(__doc__) | |
| sys.exit(2) | |
| model, src, out = sys.argv[1], sys.argv[2], sys.argv[3] | |
| base = sys.argv[4] if len(sys.argv) > 4 else "http://localhost:11434" | |
| samples = [json.loads(l) for l in open(src, encoding="utf-8") if l.strip()] | |
| with open(out, "w", encoding="utf-8") as fo: | |
| for i, s in enumerate(samples, 1): | |
| msgs = [m for m in s["messages"] if m["role"] != "assistant"] | |
| t0 = time.time() | |
| r = requests.post( | |
| f"{base}/api/chat", | |
| json={ | |
| "model": model, | |
| "messages": msgs, | |
| "stream": False, | |
| "options": {"temperature": 0, "num_ctx": 4096, "num_predict": 256}, | |
| }, | |
| timeout=300, | |
| ).json() | |
| exp = next(m["content"] for m in s["messages"] if m["role"] == "assistant") | |
| fo.write( | |
| json.dumps( | |
| { | |
| "id": s.get("id", f"sample_{i}"), | |
| "prompt": msgs[-1]["content"], | |
| "expected": exp, | |
| "raw": r.get("message", {}).get("content", ""), | |
| "eval_count": r.get("eval_count"), | |
| "eval_duration_ns": r.get("eval_duration"), | |
| "wall_s": time.time() - t0, | |
| }, | |
| ensure_ascii=False, | |
| ) | |
| + "\n" | |
| ) | |
| fo.flush() | |
| print(f"[{i}/{len(samples)}] {s.get('id', i)} done", flush=True) | |
| if __name__ == "__main__": | |
| main() | |