sabaridsnfuji/Qwen3-1.7B-tamil-16bit-Instruct
TEXT GENERATIONConcurrency Cost:1Model Size:2BQuant:BF16Ctx Length:32kPublished:Jul 18, 2025License:apache-2.0Architecture:Transformer Open Weights Warm
The sabaridsnfuji/Qwen3-1.7B-tamil-16bit-Instruct is a 2 billion parameter Qwen3-based causal language model developed by sabaridsnfuji. This model is specifically finetuned for Tamil language instruction following, leveraging Unsloth for accelerated training. It is optimized for efficient deployment and performance in Tamil natural language processing tasks.
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Model Overview
The sabaridsnfuji/Qwen3-1.7B-tamil-16bit-Instruct is a 2 billion parameter Qwen3-based language model developed by sabaridsnfuji. It has been finetuned from unsloth/qwen3-1.7b-unsloth-bnb-4bit using Unsloth and Huggingface's TRL library, which enabled 2x faster training.
Key Capabilities
- Tamil Language Instruction Following: The model is specifically trained to understand and respond to instructions in Tamil.
- Efficient Training: Utilizes Unsloth for accelerated finetuning, making it a resource-efficient option for deployment.
- Qwen3 Architecture: Benefits from the underlying Qwen3 architecture, providing a strong foundation for language understanding.
Good For
- Tamil NLP Applications: Ideal for tasks requiring instruction-tuned responses in the Tamil language.
- Resource-Constrained Environments: Its efficient training and relatively smaller size (2B parameters) make it suitable for scenarios where computational resources are a consideration.
- Experimentation with Qwen3 in Tamil: Provides a ready-to-use finetuned Qwen3 model for developers working on Tamil language projects.