diffusers

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Prathik Rao 1997614aa9 avoid upcasting by assigning dtype to noise tensor (#3713 )

* avoid upcasting by assigning dtype to noise tensor

* make style

* Update train_unconditional.py

* Update train_unconditional.py

* make style

* add unit test for pickle

* revert change

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Co-authored-by: root <root@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Prathik Rao <prathikrao@microsoft.com@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>

2023-07-04 07:19:49 +05:30

text_to_image

Apply deprecations from Accelerate (#3714 )

2023-06-08 16:44:22 +02:00

textual_inversion

Apply deprecations from Accelerate (#3714 )

2023-06-08 16:44:22 +02:00

unconditional_image_generation

avoid upcasting by assigning dtype to noise tensor (#3713 )

2023-07-04 07:19:49 +05:30

README.md

refactor onnxruntime integration (#2042 )

2023-02-03 12:04:59 +01:00

README.md

Diffusers examples with ONNXRuntime optimizations

This research project is not actively maintained by the diffusers team. For any questions or comments, please contact Prathik Rao (prathikr), Sunghoon Choi (hanbitmyths), Ashwini Khade (askhade), or Peng Wang (pengwa) on github with any questions.

This aims to provide diffusers examples with ONNXRuntime optimizations for training/fine-tuning unconditional image generation, text to image, and textual inversion. Please see individual directories for more details on how to run each task using ONNXRuntime.