jihyuny/day1-train-model
TEXT GENERATIONConcurrency Cost:1Model Size:0.5BQuant:BF16Ctx Length:32kPublished:Apr 8, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The jihyuny/day1-train-model is a 0.5 billion parameter Qwen2.5-Instruct causal language model, developed by jihyuny. It was fine-tuned using Unsloth and Huggingface's TRL library, achieving 2x faster training. With a 32768 token context length, this model is optimized for efficient instruction-following tasks.
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Overview
The jihyuny/day1-train-model is a 0.5 billion parameter Qwen2.5-Instruct model, fine-tuned by jihyuny. It leverages the Unsloth library and Huggingface's TRL for efficient training, resulting in a 2x speed improvement compared to standard methods. The model maintains a substantial context length of 32768 tokens, making it suitable for tasks requiring extensive input.
Key Capabilities
- Efficient Instruction Following: Optimized for processing and responding to instructions.
- Fast Training: Benefits from Unsloth's optimizations for quicker fine-tuning.
- Extended Context: Supports a 32768 token context window for complex prompts.
Good For
- Applications requiring a compact yet capable instruction-tuned model.
- Scenarios where rapid fine-tuning and deployment are critical.
- Tasks that benefit from a large context window on a smaller model.