JihoonKim5484/day1-train-model
TEXT GENERATIONConcurrency Cost:1Model Size:0.5BQuant:BF16Ctx Length:32kPublished:Mar 25, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
JihoonKim5484/day1-train-model is a 0.5 billion parameter Qwen2.5-Instruct causal language model developed by JihoonKim5484. This model was fine-tuned using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is suitable for tasks requiring a compact, efficiently trained instruction-following model.
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Model Overview
JihoonKim5484/day1-train-model is a 0.5 billion parameter instruction-tuned language model based on the Qwen2.5 architecture. Developed by JihoonKim5484, this model was fine-tuned from unsloth/Qwen2.5-0.5B-Instruct-unsloth-bnb-4bit.
Key Characteristics
- Efficient Training: The model was trained with Unsloth and Huggingface's TRL library, resulting in a 2x faster fine-tuning process compared to standard methods.
- Compact Size: With 0.5 billion parameters, it offers a smaller footprint suitable for resource-constrained environments or applications where inference speed is critical.
- Instruction Following: As an instruction-tuned model, it is designed to understand and execute commands given in natural language.
Good For
- Applications requiring a lightweight and fast instruction-following model.
- Experimentation with efficient fine-tuning techniques using Unsloth.
- Tasks where a smaller model size is advantageous for deployment or cost-effectiveness.