huseyinatahaninan/appworld_distillation_sft-SFT-Qwen3-8B
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kPublished:Jan 20, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The huseyinatahaninan/appworld_distillation_sft-SFT-Qwen3-8B is an 8 billion parameter language model, fine-tuned from the Qwen/Qwen3-8B architecture. It was trained on the appworld_distillation_sft dataset, achieving a validation loss of 0.2667. This model is specialized for tasks related to its specific fine-tuning dataset, making it suitable for applications requiring knowledge or generation aligned with 'appworld_distillation_sft' content.
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Model Overview
huseyinatahaninan/appworld_distillation_sft-SFT-Qwen3-8B is an 8 billion parameter language model, fine-tuned from the base Qwen/Qwen3-8B architecture. This model has been specifically adapted through supervised fine-tuning (SFT) on the appworld_distillation_sft dataset.
Key Capabilities
- Specialized Knowledge: Optimized for tasks and content related to the
appworld_distillation_sftdomain due to its targeted training. - Qwen3-8B Foundation: Benefits from the robust capabilities of the Qwen3-8B base model, including a 32768-token context length.
- Fine-tuned Performance: Achieved a validation loss of 0.2667 during training, indicating effective learning on its specific dataset.
Good for
- Domain-Specific Applications: Ideal for use cases that require understanding or generation within the 'appworld_distillation_sft' context.
- Research and Development: Suitable for researchers exploring the impact of distillation and SFT on specific datasets using the Qwen3-8B architecture.
- Custom AI Solutions: Can serve as a strong foundation for building applications that need a model with focused expertise derived from its training data.