tianbuyung/qwen2.5-3b-instruct-indonesia
TEXT GENERATIONConcurrent Unit Cost:1Model Size:3.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 16, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The tianbuyung/qwen2.5-3b-instruct-indonesia is a 3.1 billion parameter instruction-tuned causal language model, developed by tianbuyung. This model is finetuned from unsloth/Qwen2.5-3B-bnb-4bit and optimized for faster training using Unsloth and Huggingface's TRL library. It is specifically designed for instruction-following tasks, leveraging its efficient training methodology.
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Overview
The tianbuyung/qwen2.5-3b-instruct-indonesia is a 3.1 billion parameter instruction-tuned language model. It was developed by tianbuyung and is based on the Qwen2.5 architecture, specifically finetuned from the unsloth/Qwen2.5-3B-bnb-4bit model.
Key Characteristics
- Efficient Training: This model was trained significantly faster using Unsloth and Huggingface's TRL library, indicating an optimization for resource-efficient fine-tuning.
- Instruction-Tuned: Designed to follow instructions effectively, making it suitable for various prompt-based applications.
- Base Model: Built upon the Qwen2.5-3B architecture, providing a solid foundation for its language capabilities.
Use Cases
This model is particularly well-suited for applications requiring:
- Instruction following in Indonesian.
- Deployment in environments where a smaller, efficiently trained model is beneficial.
- Tasks that can leverage its instruction-tuned nature for generating responses based on specific prompts.