MooJae/day1-train-model
TEXT GENERATIONConcurrency Cost:1Model Size:0.5BQuant:BF16Ctx Length:32kPublished:Apr 8, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
MooJae/day1-train-model is a 0.5 billion parameter Qwen2-based instruction-tuned causal language model developed by MooJae. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is optimized for efficient deployment and tasks requiring a compact yet capable language model.
Loading preview...
Overview
MooJae/day1-train-model is a compact 0.5 billion parameter instruction-tuned language model based on the Qwen2 architecture. Developed by MooJae, this model was fine-tuned using the Unsloth library in conjunction with Huggingface's TRL library. A key differentiator of this model's development is its training efficiency, achieving a 2x speedup during the fine-tuning process.
Key Capabilities
- Efficient Fine-tuning: Leverages Unsloth for significantly faster training times compared to standard methods.
- Qwen2 Architecture: Benefits from the robust and performant base architecture of Qwen2.
- Instruction-Tuned: Designed to follow instructions effectively for various NLP tasks.
Good For
- Resource-Constrained Environments: Its small parameter count makes it suitable for deployment where computational resources are limited.
- Rapid Prototyping: The accelerated training process allows for quicker iteration and experimentation.
- Specific Instruction-Following Tasks: Ideal for applications requiring a compact model to execute given instructions efficiently.