Instructions to use RichardErkhov/Limby_-_model-gguf 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 RichardErkhov/Limby_-_model-gguf 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 RichardErkhov/Limby_-_model-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf RichardErkhov/Limby_-_model-gguf:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf RichardErkhov/Limby_-_model-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf RichardErkhov/Limby_-_model-gguf: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 RichardErkhov/Limby_-_model-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf RichardErkhov/Limby_-_model-gguf: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 RichardErkhov/Limby_-_model-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf RichardErkhov/Limby_-_model-gguf:Q4_K_M
Use Docker
docker model run hf.co/RichardErkhov/Limby_-_model-gguf:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use RichardErkhov/Limby_-_model-gguf with Ollama:
ollama run hf.co/RichardErkhov/Limby_-_model-gguf:Q4_K_M
- Unsloth Desktop
- Pi
How to use RichardErkhov/Limby_-_model-gguf with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf RichardErkhov/Limby_-_model-gguf: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": "RichardErkhov/Limby_-_model-gguf:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use RichardErkhov/Limby_-_model-gguf with Docker Model Runner:
docker model run hf.co/RichardErkhov/Limby_-_model-gguf:Q4_K_M
- Lemonade
How to use RichardErkhov/Limby_-_model-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull RichardErkhov/Limby_-_model-gguf:Q4_K_M
Run and chat with the model
lemonade run user.Limby_-_model-gguf-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use RichardErkhov/Limby_-_model-gguf with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf RichardErkhov/Limby_-_model-gguf: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 RichardErkhov/Limby_-_model-gguf:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use RichardErkhov/Limby_-_model-gguf with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf RichardErkhov/Limby_-_model-gguf: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 "RichardErkhov/Limby_-_model-gguf: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"
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Quantization made by Richard Erkhov.
model - GGUF
- Model creator: https://huggingface.co/Limby/
- Original model: https://huggingface.co/Limby/model/
| Name | Quant method | Size |
|---|---|---|
| model.Q2_K.gguf | Q2_K | 0.32GB |
| model.IQ3_XS.gguf | IQ3_XS | 0.32GB |
| model.IQ3_S.gguf | IQ3_S | 0.32GB |
| model.Q3_K_S.gguf | Q3_K_S | 0.32GB |
| model.IQ3_M.gguf | IQ3_M | 0.32GB |
| model.Q3_K.gguf | Q3_K | 0.33GB |
| model.Q3_K_M.gguf | Q3_K_M | 0.33GB |
| model.Q3_K_L.gguf | Q3_K_L | 0.34GB |
| model.IQ4_XS.gguf | IQ4_XS | 0.33GB |
| model.Q4_0.gguf | Q4_0 | 0.33GB |
| model.IQ4_NL.gguf | IQ4_NL | 0.33GB |
| model.Q4_K_S.gguf | Q4_K_S | 0.36GB |
| model.Q4_K.gguf | Q4_K | 0.37GB |
| model.Q4_K_M.gguf | Q4_K_M | 0.37GB |
| model.Q4_1.gguf | Q4_1 | 0.35GB |
| model.Q5_0.gguf | Q5_0 | 0.37GB |
| model.Q5_K_S.gguf | Q5_K_S | 0.38GB |
| model.Q5_K.gguf | Q5_K | 0.39GB |
| model.Q5_K_M.gguf | Q5_K_M | 0.39GB |
| model.Q5_1.gguf | Q5_1 | 0.39GB |
| model.Q6_K.gguf | Q6_K | 0.47GB |
| model.Q8_0.gguf | Q8_0 | 0.49GB |
Original model description:
base_model: unsloth/qwen2.5-0.5b-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - qwen2 - trl - sft
Uploaded model
- Developed by: Limby
- License: apache-2.0
- Finetuned from model : unsloth/qwen2.5-0.5b-bnb-4bit
This qwen2 model was trained 2x faster with Unsloth and Huggingface's TRL library.
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