Instructions to use Shome/croguana-RC2-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Shome/croguana-RC2-gguf with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Shome/croguana-RC2-gguf")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Shome/croguana-RC2-gguf", dtype="auto")

llama-cpp-python

How to use Shome/croguana-RC2-gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Shome/croguana-RC2-gguf",
	filename="unsloth.Q5_K_M.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use Shome/croguana-RC2-gguf with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Shome/croguana-RC2-gguf:Q5_K_M
# Run inference directly in the terminal:
llama-cli -hf Shome/croguana-RC2-gguf:Q5_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Shome/croguana-RC2-gguf:Q5_K_M
# Run inference directly in the terminal:
llama-cli -hf Shome/croguana-RC2-gguf:Q5_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 Shome/croguana-RC2-gguf:Q5_K_M
# Run inference directly in the terminal:
./llama-cli -hf Shome/croguana-RC2-gguf:Q5_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 Shome/croguana-RC2-gguf:Q5_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Shome/croguana-RC2-gguf:Q5_K_M

Use Docker

docker model run hf.co/Shome/croguana-RC2-gguf:Q5_K_M

LM Studio
Jan

vLLM

How to use Shome/croguana-RC2-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Shome/croguana-RC2-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Shome/croguana-RC2-gguf",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Shome/croguana-RC2-gguf:Q5_K_M

SGLang

How to use Shome/croguana-RC2-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 "Shome/croguana-RC2-gguf" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Shome/croguana-RC2-gguf",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "Shome/croguana-RC2-gguf" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Shome/croguana-RC2-gguf",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use Shome/croguana-RC2-gguf with Ollama:
```
ollama run hf.co/Shome/croguana-RC2-gguf:Q5_K_M
```

Unsloth Studio new

How to use Shome/croguana-RC2-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 Shome/croguana-RC2-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 Shome/croguana-RC2-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Shome/croguana-RC2-gguf to start chatting

Docker Model Runner
How to use Shome/croguana-RC2-gguf with Docker Model Runner:
```
docker model run hf.co/Shome/croguana-RC2-gguf:Q5_K_M
```

Lemonade

How to use Shome/croguana-RC2-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Shome/croguana-RC2-gguf:Q5_K_M

Run and chat with the model

lemonade run user.croguana-RC2-gguf-Q5_K_M

List all available models

lemonade list

⚠️ VAŽNA OBAVIJEST / IMPORTANT NOTICE

OGRANIČENJE ODGOVORNOSTI (DISCLAIMER) ZA KORISNIKE U RH

Ovaj model (CroGuana) je eksperimentalni istraživački projekt i NIJE namijenjen za produkcijsku upotrebu. Korištenjem modela prihvaćate sljedeće uvjete:

Istraživačka namjena: Model je razvijen isključivo u svrhe testiranja obrade hrvatskog jezika (NLP). Zabranjena je uporaba u komercijalne svrhe bez dodatnih sigurnosnih provjera.

Zabrana kritične primjene: Izričito je ZABRANJENO korištenje modela u sustavima koji mogu ugroziti život, zdravlje ili imovinu (npr. medicina, pravo, upravljanje strojevima, automatizirano donošenje odluka).

Nepredvidljivost: Model može generirati netočne, pristrane ili opasne informacije (hallucinations). Autor ne jamči za točnost izlaza.

Isključenje odgovornosti: Sukladno prijedlozima Zakona o provedbi Uredbe o AI u RH, autor (Tomislav Kraljević Shome) se u potpunosti odriče bilo kakve građanske ili kaznene odgovornosti za štetu (uključujući uništenje imovine) nastalu korištenjem ovog modela protivno navedenim uputama.

Odgovornost korisnika: Korisnik koji model "stavlja u pogon" ili integrira u druge sustave preuzima punu odgovornost za usklađenost s Aktom o AI i lokalnim zakonima.

Uploaded model

Developed by: Shome
License: cc-by-sa-4.0
Finetuned from model : gordicaleksa/YugoGPT

Model prompt:

"### Korisnik:\n[upit]\n### AI asistent:\n[odgovor]\n"

Fine tuning je za chat mode, gornji template se može produžiti koliko je potrebno.

Ctx size u trainu je 8192

This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.

Downloads last month: 15

GGUF

Model size

7B params

Architecture

llama

Hardware compatibility

5-bit

Model tree for Shome/croguana-RC2-gguf

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⚠️ VAŽNA OBAVIJEST / IMPORTANT NOTICE

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