tlsrmawl/dama-aibrain

VISIONConcurrent Unit Cost:1Model Size:5.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 22, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold

The tlsrmawl/dama-aibrain is a 5.1 billion parameter Gemma-4 based language model developed by tlsrmawl, fine-tuned for general instruction following. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. With a context length of 32768 tokens, it is designed for efficient processing of longer sequences.

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Model Overview

The tlsrmawl/dama-aibrain is a 5.1 billion parameter language model, fine-tuned from the Gemma-4 architecture. Developed by tlsrmawl, this model leverages efficient training methodologies to deliver enhanced performance for various natural language processing tasks.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/gemma-4-e2b-it-unsloth-bnb-4bit, indicating its foundation in the Gemma-4 family.
  • Efficient Training: The model was trained significantly faster (2x) using Unsloth and Huggingface's TRL library, highlighting an optimization in its development process.
  • Parameter Count: Features 5.1 billion parameters, offering a balance between computational efficiency and model capability.
  • Context Length: Supports a substantial context window of 32768 tokens, suitable for handling extensive inputs and generating coherent, longer responses.

Use Cases

This model is well-suited for applications requiring a capable instruction-following language model, benefiting from its efficient training and robust context handling. Its fine-tuned nature suggests applicability in tasks where general conversational abilities and adherence to instructions are crucial.