AdrianFernandes/qwen-2.5-3b-roman-konkani-v3
TEXT GENERATIONConcurrency Cost:1Model Size:3.1BQuant:BF16Ctx Length:32kPublished:May 14, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
AdrianFernandes/qwen-2.5-3b-roman-konkani-v3 is a 3.1 billion parameter Qwen2.5-Instruct model, fine-tuned by AdrianFernandes. This model was trained using Unsloth and Huggingface's TRL library for accelerated performance. It is specifically adapted for Roman Konkani, making it suitable for tasks requiring understanding and generation in this language.
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Model Overview
AdrianFernandes/qwen-2.5-3b-roman-konkani-v3 is a specialized language model developed by AdrianFernandes. It is built upon the Qwen2.5-3B-Instruct architecture, a 3.1 billion parameter model, and has been fine-tuned for specific linguistic applications.
Key Capabilities
- Roman Konkani Language Support: This model is specifically adapted for the Roman Konkani language, indicating its primary strength in processing and generating text in this particular dialect.
- Efficient Fine-tuning: The model was fine-tuned using Unsloth and Huggingface's TRL library, which enabled a 2x faster training process compared to standard methods.
- Instruction-tuned Base: Being based on an instruction-tuned Qwen2.5 model, it is designed to follow instructions effectively for various natural language tasks.
Good For
- Roman Konkani NLP Tasks: Ideal for applications requiring language understanding, generation, or translation in Roman Konkani.
- Resource-Efficient Deployment: Its 3.1 billion parameter size makes it suitable for deployment in environments where computational resources are a consideration, while still offering specialized language capabilities.