ybpak/day1-train-model
TEXT GENERATIONConcurrency Cost:1Model Size:0.5BQuant:BF16Ctx Length:32kPublished:Apr 8, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The ybpak/day1-train-model is a 0.5 billion parameter instruction-tuned Qwen2.5 model, developed by ybpak, and fine-tuned using Unsloth and Huggingface's TRL library. This model was trained 2x faster than standard methods, leveraging Unsloth's optimization for efficient training. It is suitable for applications requiring a compact yet capable language model, particularly where rapid fine-tuning and deployment are priorities.
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ybpak/day1-train-model Overview
The ybpak/day1-train-model is a compact 0.5 billion parameter instruction-tuned language model. It is based on the Qwen2.5 architecture and was developed by ybpak.
Key Characteristics
- Base Model: Fine-tuned from
unsloth/Qwen2.5-0.5B-Instruct-unsloth-bnb-4bit. - Training Efficiency: This model was fine-tuned using Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to conventional methods.
- Parameter Count: Features 0.5 billion parameters, making it a lightweight option for various NLP tasks.
- Context Length: Supports a context length of 32768 tokens.
Use Cases
This model is particularly well-suited for:
- Applications requiring a small, efficient, and rapidly fine-tuned language model.
- Scenarios where computational resources are limited, but instruction-following capabilities are needed.
- Experimentation and development of custom instruction-tuned models, benefiting from the accelerated training methodology.