braisefernz07/konkani-qwen-lora
TEXT GENERATIONConcurrency Cost:1Model Size:3.1BQuant:BF16Ctx Length:32kPublished:Apr 16, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The braisefernz07/konkani-qwen-lora is a 3.1 billion parameter Qwen2.5-3B-Instruct model, developed by braisefernz07. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is optimized for specific applications leveraging its efficient fine-tuning process and Qwen2.5 architecture.
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Overview
The braisefernz07/konkani-qwen-lora is a 3.1 billion parameter language model based on the Qwen2.5-3B-Instruct architecture. It was developed by braisefernz07 and fine-tuned from the unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit model.
Key Capabilities
- Efficient Fine-tuning: This model was fine-tuned using Unsloth and Huggingface's TRL library, which allowed for a 2x faster training process compared to standard methods.
- Qwen2.5 Architecture: Leverages the capabilities of the Qwen2.5 instruction-tuned base model.
Good For
- Applications requiring a compact yet capable language model.
- Scenarios where efficient fine-tuning and deployment are critical.
- Further experimentation or development based on the Qwen2.5 architecture with performance enhancements from Unsloth.