Instructions to use bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF",
	filename="utter-project_EuroLLM-22B-Instruct-2512-IQ2_M.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use bartowski/utter-project_EuroLLM-22B-Instruct-2512-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 bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf bartowski/utter-project_EuroLLM-22B-Instruct-2512-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 bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf bartowski/utter-project_EuroLLM-22B-Instruct-2512-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 bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf bartowski/utter-project_EuroLLM-22B-Instruct-2512-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 bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF:Q4_K_M

Use Docker

docker model run hf.co/bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "bartowski/utter-project_EuroLLM-22B-Instruct-2512-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": "bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF:Q4_K_M

Ollama
How to use bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF with Ollama:
```
ollama run hf.co/bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF:Q4_K_M
```

Unsloth Studio

How to use bartowski/utter-project_EuroLLM-22B-Instruct-2512-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 bartowski/utter-project_EuroLLM-22B-Instruct-2512-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 bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF with Docker Model Runner:
```
docker model run hf.co/bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF:Q4_K_M
```

Lemonade

How to use bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull bartowski/utter-project_EuroLLM-22B-Instruct-2512-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.utter-project_EuroLLM-22B-Instruct-2512-GGUF-Q4_K_M

List all available models

lemonade list

utter-project_EuroLLM-22B-Instruct-2512-GGUF / utter-project_EuroLLM-22B-Instruct-2512-bf16.gguf

bartowski

Upload utter-project_EuroLLM-22B-Instruct-2512-bf16.gguf with huggingface_hub

733ce04 verified 7 months ago

Download

History Blame GGUF Editor new Delete

45.3 GB

This file is stored with Xet . It is too big to display, but you can still download it.

Xet Pointer Details

( Raw pointer file )

Xet hash:: ea1929f59792cbb0301f2570f9d32b36758e43c883a5008751fb77e05fdff028
Size of remote file:: 45.3 GB
SHA256:: 1d6b916d4f9042d18a2a1e618b0a0ee4ea40945c16ac01319ce0e6284f3a8b38

Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.