Johnnybae/dama-gusul
VISIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:5.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Sep 20, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
Johnnybae/dama-gusul is a 5.1 billion parameter language model developed by Johnnybae, fine-tuned from unsloth/gemma-4-E2B-it-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving a 2x faster training speed. It features a context length of 32768 tokens, making it suitable for applications requiring efficient processing of longer sequences.
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Overview
Johnnybae/dama-gusul is a 5.1 billion parameter language model developed by Johnnybae. It is fine-tuned from the unsloth/gemma-4-E2B-it-unsloth-bnb-4bit model, leveraging the Gemma 4 architecture.
Key Capabilities
- Efficient Training: This model was trained significantly faster, specifically 2x faster, by utilizing the Unsloth library in conjunction with Huggingface's TRL library.
- Extended Context Window: It supports a substantial context length of 32768 tokens, enabling it to handle and process longer input sequences effectively.
Good for
- Applications requiring a Gemma-based model with optimized training efficiency.
- Use cases that benefit from a large context window for processing extensive text inputs.
- Developers looking for models fine-tuned with Unsloth for faster iteration and deployment.