Instructions to use QuantFactory/KULLM3-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use QuantFactory/KULLM3-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("QuantFactory/KULLM3-GGUF", dtype="auto")

llama-cpp-python

How to use QuantFactory/KULLM3-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="QuantFactory/KULLM3-GGUF",
	filename="KULLM3.Q2_K.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use QuantFactory/KULLM3-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf QuantFactory/KULLM3-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/KULLM3-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf QuantFactory/KULLM3-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/KULLM3-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 QuantFactory/KULLM3-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/KULLM3-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 QuantFactory/KULLM3-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/KULLM3-GGUF:Q4_K_M

Use Docker

docker model run hf.co/QuantFactory/KULLM3-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use QuantFactory/KULLM3-GGUF with Ollama:
```
ollama run hf.co/QuantFactory/KULLM3-GGUF:Q4_K_M
```

Unsloth Studio new

How to use QuantFactory/KULLM3-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 QuantFactory/KULLM3-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 QuantFactory/KULLM3-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for QuantFactory/KULLM3-GGUF to start chatting

Docker Model Runner
How to use QuantFactory/KULLM3-GGUF with Docker Model Runner:
```
docker model run hf.co/QuantFactory/KULLM3-GGUF:Q4_K_M
```

Lemonade

How to use QuantFactory/KULLM3-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantFactory/KULLM3-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.KULLM3-GGUF-Q4_K_M

List all available models

lemonade list

ollama 용 Modelfile 공유 좀 해주실 수 있나요?

by SoftMS - opened Mar 30, 2025

Discussion

SoftMS

Mar 30, 2025

•

edited Mar 30, 2025

안녕하세요. 좋은 자료 제공해주셔서 정말 감사드립니다.
다름이 아니라 ollama에서 사용하기 위해 Modelfile에 작성할 Prompt Template을 찾아보기도 하고
KULLM과 ollama github문서를 각각 참고하여 직접 작성해보기도 했는데 실행을 해보면
입력과 관계없는 출력만 나오게 되어서 이렇게 요청을 드립니다.

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