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yiyixuxu
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thanks for the PR!
i left some feedbacks
yiyixuxu
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thanks!
i left a few more comments
yiyixuxu
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thanks! left two small comments
let's merge this soon
tests/models/transformers/test_models_transformer_ernie_image.py
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@claude can you do a review here also? please keep these 3 note in mind as well during your review
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I'll analyze this and get back to you. |
dg845
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Thanks for the PR! Left a few small comments.
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@bot /style |
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Style bot fixed some files and pushed the changes. |
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
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can you run |
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| # Initialize latents | ||
| if latents is None: | ||
| latents = torch.randn( |
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I think this should probably use the diffusers randn_tensor. Currently it will fail with a cpu generator which is needed for a consistent seed on different systems. ref
| return text_bth, lens | ||
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| @torch.no_grad() | ||
| def __call__( |
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Would it be possible to add support for prompt_embeds and negative_prompt_embeds which would bypass needing to encode the prompt? Ref
diffusers/src/diffusers/pipelines/z_image/pipeline_z_image.py
Lines 309 to 310 in 251676d
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@bot /style |
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Style bot fixed some files and pushed the changes. |

What does this PR do?
We have introduced a new text-to-image model called ERNIE-Image, which will soon be open-sourced to the community. This PR includes the model architecture definition, the pipeline, as well as the related documentation and test files.
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