Instructions to use mazurkin/ptn-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use mazurkin/ptn-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 mazurkin/ptn-GGUF # Run inference directly in the terminal: llama cli -hf mazurkin/ptn-GGUF
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf mazurkin/ptn-GGUF # Run inference directly in the terminal: llama cli -hf mazurkin/ptn-GGUF
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 mazurkin/ptn-GGUF # Run inference directly in the terminal: ./llama-cli -hf mazurkin/ptn-GGUF
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 mazurkin/ptn-GGUF # Run inference directly in the terminal: ./build/bin/llama-cli -hf mazurkin/ptn-GGUF
Use Docker
docker model run hf.co/mazurkin/ptn-GGUF
- LM Studio
- Jan
- Ollama
How to use mazurkin/ptn-GGUF with Ollama:
ollama run hf.co/mazurkin/ptn-GGUF
- Unsloth Studio
How to use mazurkin/ptn-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 mazurkin/ptn-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 mazurkin/ptn-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for mazurkin/ptn-GGUF to start chatting
- Docker Model Runner
How to use mazurkin/ptn-GGUF with Docker Model Runner:
docker model run hf.co/mazurkin/ptn-GGUF
- Lemonade
How to use mazurkin/ptn-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mazurkin/ptn-GGUF
Run and chat with the model
lemonade run user.ptn-GGUF-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
fine-tuning of the base LLM model with politic speaches from the website kremlin.ru, converted into GGUF, quantized as Q4KM
github
https://github.com/mazurkin/ptn
llama.cpp
Download the ptn-8B-q4km.gguf file (or ptn-8B-q8.gguf)
Run the local command line chat:
llama-cli \
--temp 0.5 \
--ctx-size 2048 \
--repeat-penalty 1.2 \
--repeat-last-n 256 \
--frequency-penalty 0.5 \
--presence-penalty 0.5 \
--model "ptn-8B-q4km.gguf"
As alternative run the local web-server chat:
llama-server \
--temp 0.5 \
--ctx-size 2048 \
--repeat-penalty 1.2 \
--repeat-last-n 256 \
--frequency-penalty 0.5 \
--presence-penalty 0.5 \
--host 127.0.0.1 \
--port 8080 \
--model "ptn-8B-q4km.gguf"
ollama
Download the ptn-8B-q4km.gguf file and the ptn-8B-q4km.ollama file
Create a local model first:
ollama create ptn-8B-q4km -f ./ptn-8B-q4km.ollama
Run the model:
ollama run ptn-8B-q4km
example
Q: как лучше всего пропатчить KDE под FreeBSD?
A: Не знаю, не могу вам сказать. Это очень специальные вещи и вопросы: как правильно настроить то или другое программное обеспечение на той либо иной платформе – это уже специалисты должны заниматься конкретно этим продуктом в данной операционной системе.
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We're not able to determine the quantization variants.
Model tree for mazurkin/ptn-GGUF
Base model
yandex/YandexGPT-5-Lite-8B-pretrain