Instructions to use INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-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 INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-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 INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-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 INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-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 INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-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 INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF:Q4_K_M
Use Docker
docker model run hf.co/INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-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": "INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF:Q4_K_M
- Ollama
How to use INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF with Ollama:
ollama run hf.co/INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF:Q4_K_M
- Unsloth Studio
How to use INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-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 INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-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 INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF with Docker Model Runner:
docker model run hf.co/INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF:Q4_K_M
- Lemonade
How to use INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.MamayLM-Gemma-3-27B-IT-v2.0-GGUF-Q4_K_M
List all available models
lemonade list
Emiliyan Pavlov commited on
Update model card
Browse files
README.md
ADDED
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---
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license: gemma
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pipeline_tag: image-text-to-text
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base_model: INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0
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tags:
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- gemma3
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- uk
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- ukrainian
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- gguf
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language:
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- uk
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- en
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---
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# MamayLM-Gemma-3-27B-IT-v2.0-GGUF
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GGUF quantized versions of [MamayLM-Gemma-3-27B-IT-v2.0](https://huggingface.co/INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0) for use with llama.cpp, Ollama, LM Studio, and other GGUF-compatible tools. MamayLM v2.0 is a series of Ukrainian-adapted LLMs based on Gemma 3, developed by [INSAIT](https://insait.ai).
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**Blog post**: [MamayLM v2.0 Release](https://models.mamay.ai/blog/mamaylm-v2-release-en/)
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### Key improvements over MamayLM v1.0
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1. **Vision-language understanding** — The model understands both text and images within the same context.
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2. **Instruction-following** — Trained on a broader range of tasks, multi-turn conversations, complex instructions, and system prompts.
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3. **Longer context** — Effective context of 131k tokens for longer conversations and complex instructions.
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4. **Updated knowledge cut-off** — Pretraining data up to May 2025, instruction fine-tuning up to October 2025.
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## Available quantizations
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| Filename | Quant type | Description |
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|----------|-----------|-------------|
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| `MamayLM-Gemma-3-27B-IT-v2.0-Q4_K_M.gguf` | Q4_K_M | Good balance of quality and size — **recommended** |
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| `MamayLM-Gemma-3-27B-IT-v2.0-Q5_K_M.gguf` | Q5_K_M | High quality, slightly larger |
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| `MamayLM-Gemma-3-27B-IT-v2.0-Q6_K.gguf` | Q6_K | Very high quality, near lossless |
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| `MamayLM-Gemma-3-27B-IT-v2.0-Q8_0.gguf` | Q8_0 | Essentially lossless |
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## Usage
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### llama.cpp
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```bash
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# Download a specific quantization
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huggingface-cli download INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF \
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--include "MamayLM-Gemma-3-27B-IT-v2.0-Q4_K_M.gguf" \
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--local-dir .
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# Run with llama-cli
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llama-cli -m MamayLM-Gemma-3-27B-IT-v2.0-Q4_K_M.gguf \
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-p "Коли був заснований Київський університет?" \
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-n 512
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```
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### Ollama
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Create a `Modelfile`:
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```
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FROM ./MamayLM-Gemma-3-27B-IT-v2.0-Q4_K_M.gguf
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```
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Then:
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```bash
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ollama create mamaylm-gemma3-27b-v2.0 -f Modelfile
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ollama run mamaylm-gemma3-27b-v2.0
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```
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### LM Studio
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Search for `MamayLM-Gemma-3-27B-IT-v2.0-GGUF` in the model browser, or download a GGUF file manually and load it.
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## Download
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```bash
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# Download all quantizations
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huggingface-cli download INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF
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# Download a specific file
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huggingface-cli download INSAIT-Institute/MamayLM-Gemma-3-27B-IT-v2.0-GGUF \
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--include "MamayLM-Gemma-3-27B-IT-v2.0-Q4_K_M.gguf" \
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--local-dir .
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```
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## License
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MamayLM-Gemma-3-27B-IT-v2.0-GGUF is distributed under the [Gemma Terms of Use](https://ai.google.dev/gemma/terms).
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