heeaiworld/dama-aibrain
heeaiworld/dama-aibrain is a 5.1 billion parameter instruction-tuned causal language model developed by heeaiworld. This model is finetuned from unsloth/gemma-4-e2b-it-unsloth-bnb-4bit, leveraging Unsloth and Huggingface's TRL library for accelerated training. It offers a 32768 token context length, making it suitable for tasks requiring extensive contextual understanding.
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Model Overview
heeaiworld/dama-aibrain is a 5.1 billion parameter instruction-tuned language model developed by heeaiworld. It is finetuned from the unsloth/gemma-4-e2b-it-unsloth-bnb-4bit base model, utilizing the Unsloth library and Huggingface's TRL for efficient training. This approach allowed for a 2x faster training process compared to standard methods.
Key Characteristics
- Parameter Count: 5.1 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a substantial context window of 32768 tokens, enabling the model to process and generate longer sequences of text.
- Training Efficiency: Benefits from Unsloth's optimizations, resulting in significantly faster finetuning.
- License: Released under the Apache-2.0 license, allowing for broad use and distribution.
Use Cases
This model is well-suited for applications requiring a capable instruction-tuned language model with a large context window. Its efficient training process suggests potential for further finetuning on specific downstream tasks. Developers looking for a Gemma-based model with optimized training and a generous context length may find this model particularly useful for various NLP applications.