Unverified50% confidenceFactExact time
Large model fine-tuning engineers (SFT direction) are one of the fastest-growing areas of enterprise demand, because enterprises often perform SFT supervised fine-tuning and LoRA fine-tuning on existing models using internal data rather than training models from scratch.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
9/17/2026
First Seen
Valid until: 12/16/2026
Sources
Related Entities
Related Claims
UnverifiedSupervised Fine-Tuning (SFT) trains the model using 'prompt-response' example pairs, teaching the model to respond in a conversational format, thereby making outputs more coherent.71% similarUnverifiedModel optimization directions include SFT supervised fine-tuning, reinforcement learning and DPO alignment, and data cleaning and data quality management.71% similarUnverified微调技术允许企业在原有模型基础上用私有数据进行二次训练以定制模型行为66% similarUnverifiedEnterprises can use the outputs of closed-source models to build training datasets, and then transfer large model capabilities to private small models through knowledge distillation.65% similarUnverifiedBase models refer to general-purpose large language models such as GPT, Doubao, and DeepSeek, while post-trained models refer to models fine-tuned for specific industries based on base models.64% similar
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