Instructions to use DeepSeekOracle/lygo-console-models 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 DeepSeekOracle/lygo-console-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 DeepSeekOracle/lygo-console-models # Run inference directly in the terminal: llama cli -hf DeepSeekOracle/lygo-console-models
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf DeepSeekOracle/lygo-console-models # Run inference directly in the terminal: llama cli -hf DeepSeekOracle/lygo-console-models
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 DeepSeekOracle/lygo-console-models # Run inference directly in the terminal: ./llama-cli -hf DeepSeekOracle/lygo-console-models
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 DeepSeekOracle/lygo-console-models # Run inference directly in the terminal: ./build/bin/llama-cli -hf DeepSeekOracle/lygo-console-models
Use Docker
docker model run hf.co/DeepSeekOracle/lygo-console-models
- LM Studio
- Jan
- Ollama
How to use DeepSeekOracle/lygo-console-models with Ollama:
ollama run hf.co/DeepSeekOracle/lygo-console-models
- Unsloth Desktop
- Pi
How to use DeepSeekOracle/lygo-console-models with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf DeepSeekOracle/lygo-console-models
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": "DeepSeekOracle/lygo-console-models" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use DeepSeekOracle/lygo-console-models with Docker Model Runner:
docker model run hf.co/DeepSeekOracle/lygo-console-models
- Lemonade
How to use DeepSeekOracle/lygo-console-models with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull DeepSeekOracle/lygo-console-models
Run and chat with the model
lemonade run user.lygo-console-models-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use DeepSeekOracle/lygo-console-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 DeepSeekOracle/lygo-console-models
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 DeepSeekOracle/lygo-console-models
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use DeepSeekOracle/lygo-console-models with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf DeepSeekOracle/lygo-console-models
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 "DeepSeekOracle/lygo-console-models" \ --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"
File size: 3,883 Bytes
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"lock_version": 1,
"product": "LYGO Local Agent Console",
"signature": "Δ9Φ963-LYGO-LLM-CONSOLE-v1",
"updated": "2026-09-20",
"note": "Owned by the steward. The fetcher reads ONLY the hosts below - never a third party URL - and verifies sha256 before a file lands. Weights stay with their authors' licences; they are redistributed here with licence text and attribution kept intact.",
"hosts": {
"primary": "https://huggingface.co/DeepSeekOracle/lygo-console-models/resolve/0bc1e1f1761dcf6a732a0f3202aaf6b3b754f9de/",
"primary_raw": "https://huggingface.co/DeepSeekOracle/lygo-console-models/raw/0bc1e1f1761dcf6a732a0f3202aaf6b3b754f9de/",
"mirror": "https://github.com/DeepSeekOracle/lygo-console-models/releases/latest/download/",
"repo_page": "https://huggingface.co/DeepSeekOracle/lygo-console-models",
"mirror_page": "https://github.com/DeepSeekOracle/lygo-console-models",
"revision": "0bc1e1f1761dcf6a732a0f3202aaf6b3b754f9de",
"revision_note": "Pinned to one commit on purpose: nobody (us included) can swap what this lock serves. Changing a model means a new lock, and a new build.",
"mirror_files": ["LICENSE-APACHE-2.0.txt", "fetch_models.py", "models.lock.json", "gemma4-12b-mmproj.gguf", "nomic-embed-text-latest.gguf"],
"license_text": "https://www.apache.org/licenses/LICENSE-2.0.txt"
},
"profiles": {
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"basic": ["gemma4-12b", "gemma4-12b-mmproj", "nomic-embed-text"],
"full": ["gemma4-12b", "gemma4-12b-mmproj", "nomic-embed-text", "qwen2.5-coder-7b"],
"coder": ["qwen2.5-coder-7b"],
"embed": ["nomic-embed-text"]
},
"models": [
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"role": "brain",
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"upstream": "google/gemma-4-12b (GGUF conversion)",
"modalities": ["text", "image", "audio"],
"context_tokens": 262144,
"min_ram_gb": 10,
"note": "The shipped default. Reads pictures and audio from the same weights, runs CPU-only on a small machine."
},
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"role": "projector",
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"licence": "Apache-2.0",
"author": "Google DeepMind",
"upstream": "google/gemma-4-12b (GGUF conversion)",
"pairs_with": "gemma4-12b",
"note": "Without this file the console loses vision. It travels with the brain."
},
{
"id": "nomic-embed-text",
"vault_id": "nomic-embed-text:latest",
"role": "embed",
"kind": "model",
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"sha256": "970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6",
"licence": "Apache-2.0",
"author": "Nomic AI",
"upstream": "nomic-ai/nomic-embed-text-v1.5",
"modalities": ["text"],
"min_ram_gb": 2,
"note": "Recall / embeddings. Tiny, so it always ships with the basic set."
},
{
"id": "qwen2.5-coder-7b",
"vault_id": "qwen2.5-coder:7b",
"role": "coder",
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"sha256": "60e05f2100071479f596b964f89f510f057ce397ea22f2833a0cfe029bfc2463",
"licence": "Apache-2.0",
"author": "Alibaba Qwen team",
"upstream": "Qwen/Qwen2.5-Coder-7B-Instruct (GGUF conversion)",
"modalities": ["text"],
"min_ram_gb": 8,
"note": "Optional code brain for machines with room to spare."
}
]
}
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