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Simply put, it should be reproducible with the published material. An ML model is definitely not reproducible without the training data (or a recipe to reproduc
by HPsquared 3y ago
Simply put, it should be reproducible with the published material. An ML model is definitely not reproducible without the training data (or a recipe to reproduce the training data).
- wruza 3y agoThis was said with source code and binaries in mind. Source code is easy to verify, modify and rebuild. Binaries are in practice non-modifiable, non-verifyable except for costly reverse engineering. Large models don’t work like that. The only practical way to modify (finetune, lora, merge) a model is using its binary form. A source dataset may be interesting, but it’s non-modifiable and non-reproducible in practice due to training costs. Rebuild process is usually non-deterministic, so “verify” is basically not an option. So technically true, practically complicated. Open weights and open dataset would be better terms.