maro-aigent/dama-aibrain
The maro-aigent/dama-aibrain is a 5.1 billion parameter causal language model, finetuned from unsloth/gemma-4-e2b-it-unsloth-bnb-4bit. Developed by maro-aigent, this model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It features a 32768 token context length, making it suitable for applications requiring efficient processing of longer sequences.
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Model Overview
The maro-aigent/dama-aibrain is a 5.1 billion parameter language model, developed by maro-aigent. It is finetuned from the unsloth/gemma-4-e2b-it-unsloth-bnb-4bit base model and operates under the Apache-2.0 license. A key characteristic of this model is its training methodology, which leveraged Unsloth and Huggingface's TRL library, resulting in a reported 2x acceleration during the training process.
Key Capabilities
- Efficient Training: Benefits from Unsloth's optimizations for faster training.
- Extended Context: Supports a context length of 32768 tokens, enabling processing of substantial input sequences.
Good For
- Applications requiring a 5.1B parameter model with a large context window.
- Developers interested in models trained with Unsloth for potential efficiency benefits.
- General language generation and understanding tasks where the base Gemma architecture is suitable.