Instructions to use alimkacar/werwer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use alimkacar/werwer with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="alimkacar/werwer",
	filename="unsloth.Q4_K_M.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use alimkacar/werwer 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 alimkacar/werwer:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf alimkacar/werwer:Q4_K_M

Install from WinGet (Windows)

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

Use Docker

docker model run hf.co/alimkacar/werwer:Q4_K_M

LM Studio
Jan
Ollama
How to use alimkacar/werwer with Ollama:
```
ollama run hf.co/alimkacar/werwer:Q4_K_M
```

Unsloth Studio

How to use alimkacar/werwer 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 alimkacar/werwer 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 alimkacar/werwer to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for alimkacar/werwer to start chatting

Atomic Chat new
Docker Model Runner
How to use alimkacar/werwer with Docker Model Runner:
```
docker model run hf.co/alimkacar/werwer:Q4_K_M
```

Lemonade

How to use alimkacar/werwer with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull alimkacar/werwer:Q4_K_M

Run and chat with the model

lemonade run user.werwer-Q4_K_M

List all available models

lemonade list

werwer

Commit History

(Trained with Unsloth)

101521b
verified

Alim commited on Sep 3, 2025

(Trained with Unsloth)

b99063e
verified

Alim commited on Sep 3, 2025

initial commit

5946d5a
verified

Alim commited on Sep 2, 2025

Commit History

(Trained with Unsloth) 101521b verified

(Trained with Unsloth) b99063e verified

initial commit 5946d5a verified

(Trained with Unsloth)

101521b
verified

(Trained with Unsloth)

b99063e
verified

initial commit

5946d5a
verified