Instructions to use devorah-ai-2016/dama-aibrain 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 devorah-ai-2016/dama-aibrain 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 devorah-ai-2016/dama-aibrain:Q8_0 # Run inference directly in the terminal: llama cli -hf devorah-ai-2016/dama-aibrain:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf devorah-ai-2016/dama-aibrain:Q8_0 # Run inference directly in the terminal: llama cli -hf devorah-ai-2016/dama-aibrain:Q8_0
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 devorah-ai-2016/dama-aibrain:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf devorah-ai-2016/dama-aibrain:Q8_0
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 devorah-ai-2016/dama-aibrain:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf devorah-ai-2016/dama-aibrain:Q8_0
Use Docker
docker model run hf.co/devorah-ai-2016/dama-aibrain:Q8_0
- LM Studio
- Jan
- Ollama
How to use devorah-ai-2016/dama-aibrain with Ollama:
ollama run hf.co/devorah-ai-2016/dama-aibrain:Q8_0
- Unsloth Desktop
- Docker Model Runner
How to use devorah-ai-2016/dama-aibrain with Docker Model Runner:
docker model run hf.co/devorah-ai-2016/dama-aibrain:Q8_0
- Lemonade
How to use devorah-ai-2016/dama-aibrain with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull devorah-ai-2016/dama-aibrain:Q8_0
Run and chat with the model
lemonade run user.dama-aibrain-Q8_0
List all available models
lemonade list
- Atomic Chat
Add README
Browse files
README.md
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base_model: unsloth/gemma-2-2b-it-bnb-4bit
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tags:
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- unsloth
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license: apache-2.0
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language:
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#
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- **Finetuned from model :** unsloth/gemma-2-2b-it-bnb-4bit
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[<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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tags:
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- gguf
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- llama.cpp
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- unsloth
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# dama-aibrain : GGUF
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This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
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**Example usage**:
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- For text only LLMs: `llama-cli -hf devorah-ai-2016/dama-aibrain --jinja`
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- For multimodal models: `llama-mtmd-cli -hf devorah-ai-2016/dama-aibrain --jinja`
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## Available Model files:
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- `gemma-2-2b-it.Q8_0.gguf`
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## Ollama
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An Ollama Modelfile is included for easy deployment.
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## Note
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The model's BOS token behavior was adjusted for GGUF compatibility.
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This was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth)
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[<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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