Long Text Generation Optimization Tips
A practical approach to ensuring that long texts are logically coherent:
- chunking strategy: Adoption
generate(..., max_length=256, do_sample=False)Generated in segments, add at the end of each segment"接下来请继续论述..."lead-in word - memory enhancement: Include a summary of the preceding text in the input (
"根据之前讨论的3个要点...") - Outline control: First generate
"请列出本文纲要以下是五个关键段落"Then click on Expand.
Advancement Program:
- Add in fine tuning
coherence_lossLoss function, trained using the wikisection dataset - Access to an improved version of Longformer's attention mechanism to enhance remote dependency capture
- For academic writing, predefined
section_headers=["引言","方法","结果"]compulsory structure
Effectiveness assessment tool: It is recommended that the BERTScore or Coherence-Focus scoring tool be used to quantify the effectiveness of the improvements, and the target value should be >0.85.
This answer comes from the articleQwen3-8B-BitNet: an open source language model for efficient compressionThe
May not be reproduced without permission:AI productivity tools " How to overcome the logical coherence problem of Qwen3-8B-BitNet in long text generation?
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