dadajikgu/my-brain-v2

TEXT GENERATIONConcurrent Unit Cost:1Model Size:0.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 5, 2026Architecture:Transformer Featherless Exclusive Cold

The dadajikgu/my-brain-v2 is a 0.5 billion parameter instruction-tuned language model, fine-tuned and converted to GGUF format using Unsloth. This model is optimized for efficient deployment and usage, particularly with tools like llama-cli and Ollama, offering a compact solution for various text-based applications.

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Overview

The dadajikgu/my-brain-v2 model is a 0.5 billion parameter language model that has been instruction-tuned and converted into the GGUF format. This conversion and fine-tuning process leveraged Unsloth, a framework known for accelerating training by up to 2x.

Key Features

  • Efficient Format: Provided in GGUF format, specifically qwen2.5-0.5b-instruct.Q4_K_M.gguf, which is suitable for local inference engines.
  • Unsloth Optimization: Benefits from the performance enhancements of Unsloth, indicating faster training and potentially optimized inference.
  • Ollama Support: Includes an Ollama Modelfile for straightforward deployment and integration into Ollama environments.

Usage

This model is designed for use with command-line interfaces and platforms that support GGUF models. Example usage includes:

  • Text-only LLMs: Can be run with llama-cli using the --jinja flag.
  • Ollama: Easily deployable via the provided Modelfile for local inference.