AlisonWenNCTU/sft-qwen2.5-7b-generate-thinking-no-guideline
TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kPublished:Jan 26, 2026Architecture:Transformer Cold
AlisonWenNCTU/sft-qwen2.5-7b-generate-thinking-no-guideline is a 7.6 billion parameter language model based on the Qwen2.5-7B architecture. It has been fine-tuned for 3 epochs on the nvidia/Nemotron-Cascade-SFT-Stage-2 instruction following dataset, achieving a final loss of 0.07696. This model is designed for general instruction following tasks, leveraging its base architecture and specialized SFT training.
Loading preview...
Model Overview
AlisonWenNCTU/sft-qwen2.5-7b-generate-thinking-no-guideline is a 7.6 billion parameter language model built upon the robust Qwen/Qwen2.5-7B base architecture. This model has undergone supervised fine-tuning (SFT) to enhance its instruction-following capabilities.
Key Capabilities
- Instruction Following: The model is specifically fine-tuned on the
nvidia/Nemotron-Cascade-SFT-Stage-2dataset, which is designed to improve its ability to understand and execute instructions. - Base Model Strength: Leverages the strong foundational capabilities of the Qwen2.5-7B model, providing a solid base for various natural language processing tasks.
- Training Details: Fine-tuned over 3 epochs, achieving a low final loss of 0.07696, indicating effective learning from the SFT dataset.
Good For
- General Instruction-Based Tasks: Suitable for applications requiring the model to follow specific commands or prompts.
- Building upon Qwen2.5: Offers an instruction-tuned variant of the Qwen2.5-7B model for developers seeking enhanced conversational or task-oriented performance.