Comments (1)
Hi- we picked QA fairly arbitrarily; you could try it in the other settings as well! One consideration for the generation setting is that it may be a bit more memory-intensive, as the sequences in the training data are longer. I don't know the results of applying fine-tuning in the batched setting, but you should be able to find out fairly easily with the existing codebase. Let me know if you are having trouble with that, and I'd be happy to help!
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Related Issues (12)
- How to run MEND on custom data/ custom model? HOT 4
- the QA cases comparing pre- and post- edit in paper cannot be found from the dataset, where can we find the cases, such as “Who design the Burj Khalifa?” HOT 1
- How to apply this methods to a new LMs without fine-tune? HOT 1
- How to apply MEND on T5? HOT 1
- Update Weights Operation HOT 2
- A post about your good repository in the medium HOT 1
- How to find the define of __x__ and __delta__ ? HOT 1
- About the data file in google drive HOT 2
- Can't find 10token data HOT 2
- not being able to install the requirements HOT 2
- Is it convenient for you to publish the source code for paper "Memory-Based Model Editing at Scale"? It's a pretty interesting work! HOT 1
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