maximedb/twentle-gemma-4-merged-r256-from-pretrain-silver-bf16-2
VISIONConcurrency Cost:2Model Size:31BQuant:FP8Ctx Length:32kTool Calling:SupportedPublished:Jun 17, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The maximedb/twentle-gemma-4-merged-r256-from-pretrain-silver-bf16-2 is a 31 billion parameter Gemma 4 model developed by maximedb. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language tasks, leveraging its large parameter count and 32768 token context length for robust performance.
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Overview
This model, developed by maximedb, is a 31 billion parameter Gemma 4 variant. It was fine-tuned from unsloth/gemma-4-31b-it-unsloth-bnb-4bit using the Unsloth framework and Huggingface's TRL library. A key characteristic of this model's development is its optimized training process, which was reportedly 2x faster due to the use of Unsloth.
Key Capabilities
- Large-scale language understanding: With 31 billion parameters, it is capable of handling complex language tasks.
- Efficient fine-tuning: Benefits from the Unsloth framework for faster and potentially more resource-efficient adaptation.
- Extended context window: Features a 32768 token context length, allowing for processing and generating longer texts.
Good For
- Developers looking for a Gemma 4 based model that has undergone an optimized fine-tuning process.
- Applications requiring a large parameter model with a substantial context window.
- Use cases where training efficiency during fine-tuning is a significant advantage.