Context-sensitive solutions
Effective Strategies for Preventing Disconnect in Multi-Round Conversations:
- Technical realization level: When using the dialog code template recommended in the article, be sure to keep the past_key_values parameter in the inputs, which is what the model maintains for the 1,000,000 words of contextKey mechanisms
- Application Layer Program: build a conversation history cache pool, store the token IDs of the last 5 rounds of conversations via redis, and splice the full context on each request
- Parameter tuning program: When a degradation in response quality is detected, repetition_penalty=1.2 can be dynamically adjusted to mitigate model "forgetting".
Special Note: For very long conversations (>1 hour), it is recommended to reset the attention mechanism by actively sending system alerts such as "[System] is refreshing conversation memory..." every 30 minutes. This is especially necessary in role-playing scenarios, and can be implemented with the MGRPO feature mentioned in the "Optimization Techniques" section of this article.
This answer comes from the articleTifa-DeepsexV2-7b-MGRPO: modeling support for role-playing and complex dialogues, performance beyond 32b (with one-click installer)The
May not be reproduced without permission:AI productivity tools " How to avoid Tifa-DeepsexV2-7b-MGRPO context loss in multi-round conversations?
