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#60 1 comment 0 reactions 0 assignees View on GitHub

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Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
25/100
Issue type
Feature
Clarity
Needs clarification
Activity status
Quiet

Research direction

The issue names no files, tests, or entry points. First clarify whether Tiny Auto Encoder support, GGUF quantization support, or both are in scope, then locate the relevant inference path and establish compatibility requirements. Done would require an agreed implementation scope plus evidence for the claimed memory and latency improvements.

Written by the indexing model from the issue text.

Description

Have you considered Tiny Auto Encoder for Hunyuan, Wan variant? It's a direct drop in for the vae you use that takes up a fraction of the memory and latency bandwidth. I successfully subbed it in myself to great success.

and

Did you know there are GGUF quantization options for Wan based models? I'm testing compatibility now, but I see no reason why a Q4 quant wouldn't run.

The combination of both would likely bring real time inference down to 4090 scale and trajectory rollout to laptop scale.

Just thoughts, I appreciate the project regardless.

Dominant language
Python
Stars
2.3k
Forks
254
PR merge metrics
No merged PRs in 30d

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