juwook/gemma-2b-brain-v2
VISIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:5.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Oct 8, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
juwook/gemma-2b-brain-v2 is a 5.1 billion parameter language model developed by juwook, fine-tuned from unsloth/gemma-4-E2B-it-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster fine-tuning. It offers a context length of 32768 tokens, making it suitable for applications requiring efficient processing of long sequences.
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Overview
juwook/gemma-2b-brain-v2 is a 5.1 billion parameter language model developed by juwook. It is a fine-tuned variant of the unsloth/gemma-4-E2B-it-unsloth-bnb-4bit model, leveraging the Unsloth library and Huggingface's TRL for accelerated training.
Key Capabilities
- Efficient Fine-tuning: Achieves 2x faster training speeds due to its optimization with Unsloth.
- Large Context Window: Supports a context length of 32768 tokens, enabling it to handle extensive input sequences.
- Gemma Architecture: Built upon the Gemma model family, known for its strong performance in various language tasks.
Good for
- Developers seeking a Gemma-based model with enhanced training efficiency.
- Applications requiring processing of long documents or conversations.
- Experimentation with fine-tuning techniques using Unsloth and TRL.