Marc Sun

Yes ! Here's the link to the [job](https://github.com/huggingface/transformers/actions/runs/7979164961)

Hi @ydshieh, i was able to run the tests and get the slack notification. See job [here](https://github.com/huggingface/transformers/actions/runs/7992001453). Thx for your help !

I've addressed all comments. I think that we are good to merge after I checked that the docker image is built correctly with torch 2.2.0 (currently facing some issues with...

Quick update, all tests are passing with the exception of safetensors tests. I've also implemented the quantization on the spot just like we do for bnb quantization. However, if the...

I've fixed the issues you mentioned ! LMK this looks good and I'll ask a final review from a core maintainer !

Note to the core mainteners and especially @ArthurZucker . I reverted a lot of changes I did for the serialization. I decided to postpone the serialization feature by setting the...

Closing this issue since it is solved !

Hi @moradisina, since the version [v0.20.0:](https://github.com/huggingface/accelerate/releases/tag/v0.20.0) of accelerate, `mps` device is supported with `device_map="auto"`. It should automatically map your model to `mps` device if you are using a M2 chip...

> @DN6 I think this is ready for another review now. I have gone ahead and ran the slow tests on the PixArt and DiT tests and they are passing...

> We can clearly see that the predictions in the UNet start differing and in general, producing outputs having way higher norm than the case without `device_map`. Note that the...