Arijebouraoui/nextyou-qwen-training-merged
TEXT GENERATIONConcurrency Cost:1Model Size:3.1BQuant:BF16Ctx Length:32kPublished:May 29, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
Arijebouraoui/nextyou-qwen-training-merged is a 3.1 billion parameter Qwen2 model, fine-tuned by Arijebouraoui. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster fine-tuning. It is optimized for tasks benefiting from efficient training methodologies and builds upon the Qwen2.5-3B-Instruct base model.
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Model Overview
Arijebouraoui/nextyou-qwen-training-merged is a 3.1 billion parameter language model developed by Arijebouraoui. It is fine-tuned from the unsloth/Qwen2.5-3B-Instruct-bnb-4bit base model, leveraging the Qwen2 architecture.
Key Capabilities
- Efficient Fine-tuning: This model was fine-tuned with Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
- Qwen2.5 Base: Benefits from the robust capabilities and instruction-following abilities of the Qwen2.5-3B-Instruct foundation.
Good For
- Developers seeking optimized training: Ideal for those interested in models fine-tuned with advanced, speed-enhancing techniques like Unsloth.
- Applications requiring a compact yet capable Qwen2 model: Suitable for tasks where a 3.1 billion parameter model provides sufficient performance while maintaining efficiency.
- Further experimentation with efficient fine-tuning: Can serve as a base for exploring and building upon models trained with Unsloth's accelerated methods.