Comments (6)
Unfortunately, Paella requires at least 30GB of memory since we trained on big conditoning models. We will change that in future models.
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So not even on RTX 3090? That's a pretty huge restriction if I do say so
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Definitely. Paella is not a finished research project and we are still working on improving on many things. One thing that you can do is just not load t5 at all and enable t5=False
in the sampling script. Then you can also do del clip.visual
and then it should work probably. Let me know if that works for you!
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I tried but I think there are references to t5 stuff even outside the checks for t5
, and there seem to be more complications in the Paella model with the byt5_mapper
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I managed to use Paella on colab using ~10GB of VRAM by simply using the CLIP image model to create variations, and deleting the T5 model and the prior model (I could also delete the text clip encoder).
If you have a rtx 3090 I think you can try loading the byT5-XL model alone, save the embeddings, delete the model and load the rest (if it doesn't work, try loading the model in half precision).
from paella.
I managed to use Paella on colab using ~10GB of VRAM by simply using the CLIP image model to create variations, and deleting the T5 model and the prior model (I could also delete the text clip encoder).
If you have a rtx 3090 I think you can try loading the byT5-XL model alone, save the embeddings, delete the model and load the rest (if it doesn't work, try loading the model in half precision).
Can you share your code for image variations? Thank you.
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Related Issues (20)
- How much ram is needed on cpu? HOT 2
- Removing dependency on ruDALLE? HOT 1
- would video coming soon? HOT 1
- paella_sampling.ipynb Gdown downloads dont work HOT 1
- Add Paellaaa to community section HOT 2
- Typo in Paper HOT 1
- Reproducibility of results HOT 1
- Image variation finetuned model HOT 3
- Easy to finetune for Img2Img?
- Recommended dataset size for finetuning?
- Dataset for finetuning
- Invalid link in readme
- Will higher resolution model weight release? HOT 1
- Can paella perform well on class-conditioned image generation training on ImageNet? HOT 2
- Could you provide the evaluation code?
- Is this a bug or I missed something? HOT 2
- Distributed code cannot run HOT 3
- Key error "state_dict" while loading vqgan model
- grad exposure
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