braisefernz07/qwen-konkani-final
TEXT GENERATIONConcurrency Cost:1Model Size:3.1BQuant:BF16Ctx Length:32kPublished:May 15, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The braisefernz07/qwen-konkani-final is a 3.1 billion parameter Qwen2-based causal language model developed by braisefernz07. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language generation tasks with a substantial context length of 32768 tokens.
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braisefernz07/qwen-konkani-final: A Fine-Tuned Qwen2 Model
This model, developed by braisefernz07, is a 3.1 billion parameter Qwen2-based causal language model. It was fine-tuned from unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit using the Unsloth library in conjunction with Huggingface's TRL library. This specific training methodology allowed for a 2x acceleration in the fine-tuning process.
Key Capabilities
- Efficient Fine-tuning: Leverages Unsloth for significantly faster training times.
- Qwen2 Architecture: Built upon the robust Qwen2 model family.
- Large Context Window: Supports a context length of 32768 tokens, suitable for processing extensive inputs.
Good For
- Applications requiring a compact yet capable language model.
- Scenarios where efficient fine-tuning is a priority.
- Tasks benefiting from a large context window for understanding and generating longer texts.