Instructions to use Puujeeeeeeeeeeee/gemma4-e4b-base-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 Puujeeeeeeeeeeee/gemma4-e4b-base-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 Puujeeeeeeeeeeee/gemma4-e4b-base-gguf:BF16 # Run inference directly in the terminal: llama cli -hf Puujeeeeeeeeeeee/gemma4-e4b-base-gguf:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Puujeeeeeeeeeeee/gemma4-e4b-base-gguf:BF16 # Run inference directly in the terminal: llama cli -hf Puujeeeeeeeeeeee/gemma4-e4b-base-gguf:BF16
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 Puujeeeeeeeeeeee/gemma4-e4b-base-gguf:BF16 # Run inference directly in the terminal: ./llama-cli -hf Puujeeeeeeeeeeee/gemma4-e4b-base-gguf:BF16
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 Puujeeeeeeeeeeee/gemma4-e4b-base-gguf:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Puujeeeeeeeeeeee/gemma4-e4b-base-gguf:BF16
Use Docker
docker model run hf.co/Puujeeeeeeeeeeee/gemma4-e4b-base-gguf:BF16
- LM Studio
- Jan
- Ollama
How to use Puujeeeeeeeeeeee/gemma4-e4b-base-gguf with Ollama:
ollama run hf.co/Puujeeeeeeeeeeee/gemma4-e4b-base-gguf:BF16
- Unsloth Desktop
- Docker Model Runner
How to use Puujeeeeeeeeeeee/gemma4-e4b-base-gguf with Docker Model Runner:
docker model run hf.co/Puujeeeeeeeeeeee/gemma4-e4b-base-gguf:BF16
- Lemonade
How to use Puujeeeeeeeeeeee/gemma4-e4b-base-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Puujeeeeeeeeeeee/gemma4-e4b-base-gguf:BF16
Run and chat with the model
lemonade run user.gemma4-e4b-base-gguf-BF16
List all available models
lemonade list
- Atomic Chat
File size: 1,160 Bytes
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tags:
- gguf
- llama.cpp
- unsloth
- vision-language-model
---
# gemma4-e4b-base-gguf : GGUF
This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
**Example usage**:
- For text only LLMs: `llama-cli -hf Puujeeeeeeeeeeee/gemma4-e4b-base-gguf --jinja`
- For multimodal models: `llama-mtmd-cli -hf Puujeeeeeeeeeeee/gemma4-e4b-base-gguf --jinja`
## Available Model files:
- `gemma-4-E4B.Q4_K_M.gguf`
- `gemma-4-E4B.BF16-mmproj.gguf`
## ⚠️ Ollama Note for Vision Models
**Important:** Ollama currently does not support separate mmproj files for vision models.
To create an Ollama model from this vision model:
1. Place the `Modelfile` in the same directory as the finetuned bf16 merged model
3. Run: `ollama create model_name -f ./Modelfile`
(Replace `model_name` with your desired name)
This will create a unified bf16 model that Ollama can use.
This was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth)
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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