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"
Download models.lock.json from DeepSeekOracle/lygo-console-models: direct link, hf CLI and curl.
- Browser
- Download file 3.88 kB
-
https://huggingface.co/DeepSeekOracle/lygo-console-models/resolve/main/models.lock.json
- Command line
-
hf download hf://DeepSeekOracle/lygo-console-models/models.lock.json
-
curl -L -o models.lock.json https://huggingface.co/DeepSeekOracle/lygo-console-models/resolve/main/models.lock.json
3.88 kB
| { | |
| "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": { | |
| "core": ["gemma4-12b", "gemma4-12b-mmproj"], | |
| "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": [ | |
| { | |
| "id": "gemma4-12b", | |
| "vault_id": "gemma4:12b", | |
| "role": "brain", | |
| "kind": "model", | |
| "file": "gemma4-12b.gguf", | |
| "bytes": 7381382048, | |
| "sha256": "1278394b693672ac2799eadc9a83fd98259a6a88a40acfb1dcaa6c6fc895a606", | |
| "licence": "Apache-2.0", | |
| "author": "Google DeepMind", | |
| "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." | |
| }, | |
| { | |
| "id": "gemma4-12b-mmproj", | |
| "vault_id": "gemma4:12b", | |
| "role": "projector", | |
| "kind": "mmproj", | |
| "file": "gemma4-12b-mmproj.gguf", | |
| "bytes": 175115584, | |
| "sha256": "675ad6e68101ca9413ec806855c452362f0213f2dfc5800996b086fdb8119842", | |
| "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", | |
| "file": "nomic-embed-text-latest.gguf", | |
| "bytes": 274290656, | |
| "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", | |
| "kind": "model", | |
| "file": "qwen2.5-coder-7b.gguf", | |
| "bytes": 4683074048, | |
| "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." | |
| } | |
| ] | |
| } | |