mirror of
https://github.com/invoke-ai/InvokeAI
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fc3378bb74
* refactor ckpt_to_diffuser to allow converted pipeline to remain in memory - This idea was introduced by Damian - Note that although I attempted to use the updated HuggingFace module pipelines/stable_diffusion/convert_from_ckpt.py, it was unable to convert safetensors files for reasons I didn't dig into. - Default is to extract EMA weights. * add --ckpt_convert option to load legacy ckpt files as diffusers models - not quite working - I'm getting artifacts and glitches in the converted diffuser models - leave as draft for time being * do not include safety checker in converted files * add ability to control which vae is used API now allows the caller to pass an external VAE model to the checkpoint conversion process. In this way, if an external VAE is specified in the checkpoint's config stanza, this VAE will be used when constructing the diffusers model. Tested with both regular and inpainting 1.X models. Not tested with SD 2.X models! --------- Co-authored-by: Jonathan <34005131+JPPhoto@users.noreply.github.com> Co-authored-by: Damian Stewart <null@damianstewart.com> |
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| .. | ||
| ckpt_generator | ||
| generator | ||
| restoration | ||
| __init__.py | ||
| _version.py | ||
| args.py | ||
| ckpt_to_diffuser.py | ||
| CLI.py | ||
| concepts_lib.py | ||
| conditioning.py | ||
| configure_invokeai.py | ||
| devices.py | ||
| globals.py | ||
| image_util.py | ||
| log.py | ||
| merge_diffusers.py | ||
| model_manager.py | ||
| patchmatch.py | ||
| pngwriter.py | ||
| prompt_parser.py | ||
| readline.py | ||
| seamless.py | ||
| server_legacy.py | ||
| server.py | ||
| textual_inversion_training.py | ||
| textual_inversion.py | ||
| txt2mask.py | ||