tazza11/gemma-2b-brain-v12
tazza11/gemma-2b-brain-v12 is a 2.6 billion parameter Gemma-2 based language model, fine-tuned and converted to GGUF format using Unsloth. This model is optimized for efficient deployment and inference, making it suitable for local execution via tools like llama-cli or Ollama. Its primary use case is general text generation and instruction following, leveraging the Gemma-2 architecture for robust performance in a compact size.
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Model Overview
tazza11/gemma-2b-brain-v12 is a 2.6 billion parameter language model built on the Gemma-2 architecture. It has been specifically fine-tuned and converted into the GGUF format using the Unsloth framework, which is known for accelerating training processes.
Key Characteristics
- Architecture: Based on the Gemma-2 model family.
- Parameter Count: 2.6 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports an 8192-token context window.
- Format: Provided in GGUF format, which is optimized for CPU inference and compatibility with tools like
llama-cpp-pythonandOllama. - Training Efficiency: Fine-tuned with Unsloth, indicating a potentially faster and more efficient training process.
Deployment and Usage
This model is designed for straightforward deployment, particularly for local inference. An Ollama Modelfile is included, simplifying its integration into the Ollama ecosystem. Users can interact with the model using llama-cli for text-only tasks or llama-mtmd-cli for multimodal applications, though the current model is primarily text-based. The model's BOS token behavior has been adjusted to ensure full GGUF compatibility.