Instructions to use DFveloper/AIKAR-3.1-mini-QAT-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DFveloper/AIKAR-3.1-mini-QAT-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="DFveloper/AIKAR-3.1-mini-QAT-GGUF") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("DFveloper/AIKAR-3.1-mini-QAT-GGUF") model = AutoModelForMultimodalLM.from_pretrained("DFveloper/AIKAR-3.1-mini-QAT-GGUF") - llama-cpp-python
How to use DFveloper/AIKAR-3.1-mini-QAT-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="DFveloper/AIKAR-3.1-mini-QAT-GGUF", filename="AIKAR-3-mini-Q4_0.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use DFveloper/AIKAR-3.1-mini-QAT-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 DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0 # Run inference directly in the terminal: llama cli -hf DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0 # Run inference directly in the terminal: llama cli -hf DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0
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 DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0 # Run inference directly in the terminal: ./llama-cli -hf DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0
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 DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0
Use Docker
docker model run hf.co/DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0
- LM Studio
- Jan
- vLLM
How to use DFveloper/AIKAR-3.1-mini-QAT-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DFveloper/AIKAR-3.1-mini-QAT-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": "DFveloper/AIKAR-3.1-mini-QAT-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0
- SGLang
How to use DFveloper/AIKAR-3.1-mini-QAT-GGUF with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "DFveloper/AIKAR-3.1-mini-QAT-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DFveloper/AIKAR-3.1-mini-QAT-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "DFveloper/AIKAR-3.1-mini-QAT-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DFveloper/AIKAR-3.1-mini-QAT-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Ollama
How to use DFveloper/AIKAR-3.1-mini-QAT-GGUF with Ollama:
ollama run hf.co/DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0
- Unsloth Studio
How to use DFveloper/AIKAR-3.1-mini-QAT-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for DFveloper/AIKAR-3.1-mini-QAT-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for DFveloper/AIKAR-3.1-mini-QAT-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for DFveloper/AIKAR-3.1-mini-QAT-GGUF to start chatting
- Pi
How to use DFveloper/AIKAR-3.1-mini-QAT-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use DFveloper/AIKAR-3.1-mini-QAT-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 DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0
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 DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use DFveloper/AIKAR-3.1-mini-QAT-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0
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 "DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0" \ --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"
- Docker Model Runner
How to use DFveloper/AIKAR-3.1-mini-QAT-GGUF with Docker Model Runner:
docker model run hf.co/DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0
- Lemonade
How to use DFveloper/AIKAR-3.1-mini-QAT-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull DFveloper/AIKAR-3.1-mini-QAT-GGUF:Q4_0
Run and chat with the model
lemonade run user.AIKAR-3.1-mini-QAT-GGUF-Q4_0
List all available models
lemonade list
(README.md Generated with AIKAR 3.1 mini)
AIKAR 3.1 mini
๐ ์๊ฐ
AIKAR 3.1 mini๋ ์ต์ ํ๋ ๋์์ธ์ผ๋ก ์ค๊ณ๋ ์ด๊ฒฝ๋ LLM์ ๋๋ค. ๋ฐฉ๋ํ ์์ ์ง์์ ํจ์จ์ ์ผ๋ก ์์ถํ์ฌ ์ถ๋ก ์๋๋ ๋์ด๊ณ ๋ชจ๋ธ ํฌ๊ธฐ๋ ์ต์ํํ์ต๋๋ค.
์ด ๋ชจ๋ธ์ ๋น ๋ฅด๊ณ , ๊ฐ๋ฒผ์ฐ๋ฉฐ, ๋ค์ํ ์์ง๋์ด๋ง ํ๊ฒฝ์์ ๋ฐฐํฌํ ์ ์๋๋ก ์ ์๋์์ต๋๋ค. ๋จ์ํ ์ฑ๋ด๋ถํฐ ๊ณ ์ฑ๋ฅ ์ถ๋ก ์์ ๊น์ง, AIKAR 3.1 mini๋ ๋น ๋ฅด๊ณ ํจ์จ์ ์ธ ์์ ํํธ๋๊ฐ ๋ ๊ฒ์ ๋๋ค.
โจ ์ฃผ์ ํน์ง
- โก ๋น ๋ฅธ ์ถ๋ก ์๋: 2B ํ๋ผ๋ฏธํฐ์์๋ ๋ถ๊ตฌํ๊ณ gemma 4์ ๊ณ ํจ์จ ์ํคํ ์ฒ๋ฅผ ํ์ฌํ์ฌ ๋น ๋ฅธ ์๋๋ฅผ ์๋ํฉ๋๋ค.
- ๐ ๏ธ ๊ฒฝ๋ํ: ๋ฉ๋ชจ๋ฆฌ ์ฌ์ฉ๋์ด ์ ์ด ๋ค์ํ ํ๊ฒฝ์์ ์ํํ๊ฒ ์๋ํฉ๋๋ค.
- ๐ง ๋ฐ์ด๋ ๋ฒ์ฉ์ฑ: ๋ ผ๋ฆฌ์ ์ถ๋ก , ์ฝ๋ ์์ฑ, ์ผ๋ฐ ์ง์ ๊ฒ์ ๋ฑ ๋ค์ํ ์์ ์ ์ง์ํฉ๋๋ค.
- ๐ก ๊ฐํธํ ๋ฐฐํฌ: aikar-engine์์ ์ฝ๊ฒ ๋ก๋ํ์ฌ ์ฌ์ฉํ ์ ์์ต๋๋ค.
๐ ๊ธฐ์ ์คํ
| ํญ๋ชฉ | ๋ด์ฉ |
|---|---|
| ํ๋ผ๋ฏธํฐ ์ | 2B |
| ํน์ง | ํ๊ตญ์ด ํนํ Reasoning |
| ๊ถ์ฅ ์ฌ์ฉ ์ฌ๋ก | ์ค์๊ฐ QA ์์คํ , ๊ฒฝ๋ ์ฝ๋ ์์ฑ ๋์ฐ๋ฏธ, ๋น ๋ฅธ ๋ฌธ์ ์์ฝ, ์ฃ์ง ๋๋ฐ์ด์ค ๋ฐฐํฌ |
โ๏ธ ๊ฐ๋ฐ ๊ด๋ จ ์ฐธ๊ณ ์ฌํญ
AIKAR 3.1 mini๋ ์ด๊ธฐ ๋ฒ์ ์ผ๋ก, ์ถ๋ก ๊ณผ์ ์์์ ๋ฏธ์ธํ ํธํฅ์ด ์กด์ฌํ ์ ์์ต๋๋ค. ์ค์ํ ๊ฒฐ์ ์ ํญ์ ์ ๋ขฐํ ์ ์๋ ์ถ์ฒ๋ฅผ ํตํด ๊ฒ์ฆํ์๊ธฐ ๋ฐ๋๋๋ค. ๋ํ, ๊ทน๋๋ก ๊ธด ๋ํ์์๋ ๊ธฐ์ต ์ค์๋์ด ๋ฐ์ํ ์ ์์ผ๋ฏ๋ก ๋ช ์์ ์ธ Context Re-tuning์ด ํ์ํฉ๋๋ค.
์ด ๋ชจ๋ธ์ AIKAR ๋ชจ๋ธ๊ตฐ ์ค ์ฑ๋ฅ์ ๋นํด ๊ฐ์ฅ ๋น ๋ฅด๊ฒ ์์ฉํ์ ๊ทผ์ ํ๊ณ ์๋ ๋ชจ๋ธ์ ๋๋ค. ์ฌ์ฉ์ ์ปค๋ฎค๋ํฐ์์ ๋ฐ๊ฒฌ๋๋ ๋ฒ๊ทธ๋ ๊ฐ์ ์ ์ ๋ํด์๋ ํ๋ ฅํ์ฌ ์ ๋ฐ์ดํธํ ์ ์์ต๋๋ค.
Model Family
AIKAR 3 Family
- ???
- Mini โ Edge devices
- Basic โ Everyday use
- Omni โ Balanced
- Turbo โ Fast inference (On Research)
- Large โ Advanced reasoning
- Pro โ Professional-grade (This model)
- Ultra โ Frontier model (Closed Source)
Infinite Family
- ???
- Infinite Pro โ Next-Gen (Closed Source)
- ???
๐ค ์ปค๋ฎค๋ํฐ ๋ฐ ์ฐ๋ฝ์ฒ
- Developers: LOOP Research Team
- Homepage: DFveloper.com
- Report issues: Github Issue Link
Copyright ยฉ 2026 LOOP Laboratory. Licensed under the Apache License, Version 2.0.
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