Instructions to use NotHereNorThere/Coral-2-4b 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 NotHereNorThere/Coral-2-4b 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 NotHereNorThere/Coral-2-4b:Q5_K_M # Run inference directly in the terminal: llama cli -hf NotHereNorThere/Coral-2-4b:Q5_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf NotHereNorThere/Coral-2-4b:Q5_K_M # Run inference directly in the terminal: llama cli -hf NotHereNorThere/Coral-2-4b:Q5_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 NotHereNorThere/Coral-2-4b:Q5_K_M # Run inference directly in the terminal: ./llama-cli -hf NotHereNorThere/Coral-2-4b:Q5_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 NotHereNorThere/Coral-2-4b:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf NotHereNorThere/Coral-2-4b:Q5_K_M
Use Docker
docker model run hf.co/NotHereNorThere/Coral-2-4b:Q5_K_M
- LM Studio
- Jan
- Ollama
How to use NotHereNorThere/Coral-2-4b with Ollama:
ollama run hf.co/NotHereNorThere/Coral-2-4b:Q5_K_M
- Unsloth Desktop
- Pi
How to use NotHereNorThere/Coral-2-4b with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf NotHereNorThere/Coral-2-4b:Q5_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": "NotHereNorThere/Coral-2-4b:Q5_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use NotHereNorThere/Coral-2-4b with Docker Model Runner:
docker model run hf.co/NotHereNorThere/Coral-2-4b:Q5_K_M
- Lemonade
How to use NotHereNorThere/Coral-2-4b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull NotHereNorThere/Coral-2-4b:Q5_K_M
Run and chat with the model
lemonade run user.Coral-2-4b-Q5_K_M
List all available models
lemonade list
- Hermes Agent
How to use NotHereNorThere/Coral-2-4b with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf NotHereNorThere/Coral-2-4b:Q5_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 NotHereNorThere/Coral-2-4b:Q5_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use NotHereNorThere/Coral-2-4b with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf NotHereNorThere/Coral-2-4b:Q5_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 "NotHereNorThere/Coral-2-4b:Q5_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"
Update README.md
Browse files
README.md
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- TIES
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- qlora
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- unsloth
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---
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model files soon im running the training run while typing this
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### better late than never?
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> i made the base model a few months ago and never got around to finishing it.
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yes i know, what a _goliath_ of a model (at least for the Coral family so far), but seriously it's nothing special
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- a TIES merge from several fine tunes of Qwen 3 4b
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- including the original _and_ later updated checkpoint
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- then a QLORA-merge trained on a subsection of dolphin-r1 to cement the CoT
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#
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- TIES
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- qlora
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- unsloth
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- uncensored
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---
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### better late than never?
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> i made the base model a few months ago and never got around to finishing it.
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yes i know, what a _goliath_ of a model (at least for the Coral family so far), but seriously it's nothing special
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- a TIES merge from several fine tunes of Qwen 3 4b.
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- including the original _and_ later updated checkpoint.
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- then a QLORA-merge trained on a subsection of dolphin-r1 to cement the CoT.
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# actual performance
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- it passed rigourorous vibe testing, given you use the correct infrerence/chat settings.
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- keeps qwen 3 4b's chat settings.
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- no refusal, TIES has a habit of removing post training censorship.
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- unfortunatly, thinking got steamrolled (TIES again). it still outputs \<think> formatting but theyre always empty.
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- normal 4b model limitations.
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# quant guide
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- bf16 / dont bother, just use;
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- Q5 / near lossless and fits in a lot of devices
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