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It would be really cool if we had access to the activation of weights for each key during merging. We could use the activations as a saliency map of the weights, to tell us which weight contributed more to the generation.
The way I see this working:
- pass generation parameters as input to the tool in some form (config, cli args...)
- for each key, in order:
- pass the last activations through B's key
- use the activations to decide what to merge into A
- go to the next key
Merging multiple times in a row using multiple prompts would make it possible to merge a comprehensive, wisely elected set of weights. Maybe you can even do transfer learning with this.
I am not sure how well this would really fare. I am also unsure how easy this would be to implement. Maybe instead of making model calls ourselves, we could expose some kind of api other tools interact with to share the activations of each key. This would make it possible to use comfyui or a1111 with sd-meh.
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