Text Generation
GGUF
German
English
kolibri1
quantized
experimental
llama-cpp
mixture-of-experts
conversational
Instructions to use Eliasfpv28/Kolibri-1-Q3_K_S-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 Eliasfpv28/Kolibri-1-Q3_K_S-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 Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S # Run inference directly in the terminal: llama cli -hf Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S # Run inference directly in the terminal: llama cli -hf Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S
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 Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S # Run inference directly in the terminal: ./llama-cli -hf Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S
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 Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S # Run inference directly in the terminal: ./build/bin/llama-cli -hf Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S
Use Docker
docker model run hf.co/Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S
- LM Studio
- Jan
- vLLM
How to use Eliasfpv28/Kolibri-1-Q3_K_S-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Eliasfpv28/Kolibri-1-Q3_K_S-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Eliasfpv28/Kolibri-1-Q3_K_S-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S
- Ollama
How to use Eliasfpv28/Kolibri-1-Q3_K_S-GGUF with Ollama:
ollama run hf.co/Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S
- Unsloth Desktop
- Pi
How to use Eliasfpv28/Kolibri-1-Q3_K_S-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S
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": "Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Eliasfpv28/Kolibri-1-Q3_K_S-GGUF with Docker Model Runner:
docker model run hf.co/Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S
- Lemonade
How to use Eliasfpv28/Kolibri-1-Q3_K_S-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S
Run and chat with the model
lemonade run user.Kolibri-1-Q3_K_S-GGUF-Q3_K_S
List all available models
lemonade list
- Hermes Agent
How to use Eliasfpv28/Kolibri-1-Q3_K_S-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 Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S
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 Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Eliasfpv28/Kolibri-1-Q3_K_S-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S
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 "Eliasfpv28/Kolibri-1-Q3_K_S-GGUF:Q3_K_S" \ --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 runtime-source/THIRD_PARTY_NOTICES.txt from Eliasfpv28/Kolibri-1-Q3_K_S-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 898 Bytes
-
https://huggingface.co/Eliasfpv28/Kolibri-1-Q3_K_S-GGUF/resolve/main/runtime-source/THIRD_PARTY_NOTICES.txt
- Command line
-
hf download hf://Eliasfpv28/Kolibri-1-Q3_K_S-GGUF/runtime-source/THIRD_PARTY_NOTICES.txt
-
curl -L -o THIRD_PARTY_NOTICES.txt https://huggingface.co/Eliasfpv28/Kolibri-1-Q3_K_S-GGUF/resolve/main/runtime-source/THIRD_PARTY_NOTICES.txt
898 Bytes
| This experimental source patch is independently prepared for Kolibri 1 GGUF inference. | |
| Changes made on 2026-10-03; not an upstream release. | |
| llama.cpp and GGUF implementation: MIT License. | |
| Copyright (c) 2023-2026 The ggml authors. | |
| https://github.com/ggml-org/llama.cpp/tree/edd6e2bbdad5930899a93db8fa73c3b61c7b9bcc | |
| See LICENSE-MIT.txt. The patch includes and adapts portions of this code. | |
| Kolibri inference reference: Apache-2.0. | |
| Copyright 2026 Aleph Alpha GmbH. | |
| https://github.com/Aleph-Alpha/aleph-alpha-inference/tree/049a6a7bd2405b27d6d280d256bd3d585191c7ae | |
| See LICENSE-Apache-2.0.txt. The port uses this separately licensed architecture reference. | |
| Newly prepared conversion and port additions are distributed under Apache-2.0. | |
| Existing MIT terms and attribution remain applicable to llama.cpp-derived portions. | |
| Third-party dependency licenses remain applicable when building full llama.cpp. | |