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@ -45,7 +45,7 @@ A frankensteinian amalgamation of notebooks, models and techniques for the gener
#### v5 Update: Feb 20th 2022 - gandamu / Adam Letts #### v5 Update: Feb 20th 2022 - gandamu / Adam Letts
* Added 3D animation mode. Uses weighted combination of AdaBins and MiDaS depth estimation models. Uses pytorch3d for 3D transforms on Colab and/or Linux. * Added 3D animation mode. Uses weighted combination of AdaBins and MiDaS depth estimation models. Uses pytorch3d for 3D transforms on Colab and/or Linux.
#### v5.1 Update: Mar 30th 2022 - zippy / Chris Allen and gandamu / Adam Letts / MSFTserver aka HostsServer #### v5.1 Update: Mar 30th 2022 - zippy / Chris Allen and gandamu / Adam Letts
* Integrated Turbo+Smooth features from Disco Diffusion Turbo -- just the implementation, without its defaults. * Integrated Turbo+Smooth features from Disco Diffusion Turbo -- just the implementation, without its defaults.
* Implemented resume of turbo animations in such a way that it's now possible to resume from different batch folders and batch numbers. * Implemented resume of turbo animations in such a way that it's now possible to resume from different batch folders and batch numbers.
@ -57,6 +57,13 @@ A frankensteinian amalgamation of notebooks, models and techniques for the gener
* Remove Slip Models * Remove Slip Models
* Update for crossplatform support * Update for crossplatform support
#### v5.1 Update: Apr 4th 2022 - MSFTserver aka HostsServer
* Removed pytorch3d from needing to be compiled with a lite version specifically made for Disco Diffusion
* Remove Super Resolution
* Remove Slip Models
* Update for crossplatform support
## Notebook Provenance ## Notebook Provenance
Original notebook by Katherine Crowson (https://github.com/crowsonkb, https://twitter.com/RiversHaveWings). It uses either OpenAI's 256x256 unconditional ImageNet or Katherine Crowson's fine-tuned 512x512 diffusion model (https://github.com/openai/guided-diffusion), together with CLIP (https://github.com/openai/CLIP) to connect text prompts with images. Original notebook by Katherine Crowson (https://github.com/crowsonkb, https://twitter.com/RiversHaveWings). It uses either OpenAI's 256x256 unconditional ImageNet or Katherine Crowson's fine-tuned 512x512 diffusion model (https://github.com/openai/guided-diffusion), together with CLIP (https://github.com/openai/CLIP) to connect text prompts with images.

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