Instructions to use Esobold/EsoTest_GGUFs 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 Esobold/EsoTest_GGUFs 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 Esobold/EsoTest_GGUFs:Q4_K_M # Run inference directly in the terminal: llama cli -hf Esobold/EsoTest_GGUFs:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Esobold/EsoTest_GGUFs:Q4_K_M # Run inference directly in the terminal: llama cli -hf Esobold/EsoTest_GGUFs: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 Esobold/EsoTest_GGUFs:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Esobold/EsoTest_GGUFs: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 Esobold/EsoTest_GGUFs:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Esobold/EsoTest_GGUFs:Q4_K_M
Use Docker
docker model run hf.co/Esobold/EsoTest_GGUFs:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Esobold/EsoTest_GGUFs with Ollama:
ollama run hf.co/Esobold/EsoTest_GGUFs:Q4_K_M
- Unsloth Desktop
- Pi
How to use Esobold/EsoTest_GGUFs with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Esobold/EsoTest_GGUFs: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": "Esobold/EsoTest_GGUFs:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Esobold/EsoTest_GGUFs with Docker Model Runner:
docker model run hf.co/Esobold/EsoTest_GGUFs:Q4_K_M
- Lemonade
How to use Esobold/EsoTest_GGUFs with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Esobold/EsoTest_GGUFs:Q4_K_M
Run and chat with the model
lemonade run user.EsoTest_GGUFs-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use Esobold/EsoTest_GGUFs with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Esobold/EsoTest_GGUFs: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 Esobold/EsoTest_GGUFs:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Esobold/EsoTest_GGUFs with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Esobold/EsoTest_GGUFs: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 "Esobold/EsoTest_GGUFs: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"
why no comments?
Hey kind of new to this, but shouldn't there be comments here with 6k+ of downloads?
Not really its just a test repo. If people like one they tend to discuss it elsewhere
@lawless92 Hey! Thanks for the interest in the repo - as Henk says this is mostly a spot for the outputs from a bunch of merge testing on Gemma 4 31B at the moment.
Most of the discussions tend to happen on Discord or similar, and the models here are mostly artefacts rather than full releases.
If you have questions, feel free to give me a shout!