Spyfood/Spyfood-brain-v2
Spyfood/Spyfood-brain-v2 is a 3.1 billion parameter instruction-tuned language model, fine-tuned and converted to GGUF format using Unsloth. This model is optimized for efficient deployment and inference, particularly on consumer hardware, and is suitable for general text generation tasks. Its GGUF format and included Ollama Modelfile facilitate easy integration into local inference setups.
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Spyfood-brain-v2 Overview
Spyfood/Spyfood-brain-v2 is a 3.1 billion parameter instruction-tuned language model, specifically prepared for efficient local deployment. It was fine-tuned and converted into the GGUF format using the Unsloth framework, which is known for accelerating training and conversion processes.
Key Characteristics
- Efficient Format: Provided in GGUF format, making it highly compatible with
llama.cppand related tools for CPU and GPU inference. - Optimized Training: The model benefited from Unsloth's optimizations, leading to faster training times.
- Easy Deployment: An Ollama Modelfile is included, simplifying the process of setting up and running the model with Ollama.
Usage and Deployment
This model is designed for straightforward integration into local inference environments. Users can leverage llama-cli for text-only applications or llama-mtmd-cli for multimodal scenarios, with specific instructions provided for --jinja templating. The availability of an Ollama Modelfile further streamlines deployment for users familiar with the Ollama ecosystem.