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* Added learning rate finderVolpeon2022-12-274-162/+257
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* Set default dimensions to 768; add config inheritanceVolpeon2022-12-267-26/+36
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* Code simplifications, avoid autocastVolpeon2022-12-254-82/+92
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* UpdateVolpeon2022-12-253-3/+3
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* UpdateVolpeon2022-12-241-3/+3
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* Fixed Textual InversionVolpeon2022-12-243-13/+21
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* Training updateVolpeon2022-12-243-24/+8
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* UpdateVolpeon2022-12-243-10/+26
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* FixVolpeon2022-12-241-1/+1
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* Fix againVolpeon2022-12-241-1/+1
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* FixVolpeon2022-12-242-3/+6
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* Better dataset prompt handlingVolpeon2022-12-233-11/+18
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* num_class_images is now class images per train imageVolpeon2022-12-233-4/+4
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* Improved class prompt handlingVolpeon2022-12-235-63/+31
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* FixVolpeon2022-12-231-3/+1
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* Simplified trainable embedding code againVolpeon2022-12-231-19/+6
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* Fixed and simplified trainable embeddings codeVolpeon2022-12-231-12/+12
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* Fixed Textual InversionVolpeon2022-12-223-14/+13
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* Improved Textual Inversion: Completely exclude untrained embeddings from ↵Volpeon2022-12-222-18/+76
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* Some LoRA fixes (still broken)Volpeon2022-12-212-138/+89
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* Moved common training code into separate moduleVolpeon2022-12-214-231/+203
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* Fix trainingVolpeon2022-12-205-15/+1073
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* Dependency cleanup/upgradesVolpeon2022-12-202-27/+12
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* Fix Textual Inversion dataset filteringVolpeon2022-12-201-1/+5
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* Upstream patchesVolpeon2022-12-191-5/+17
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* Improved dataset prompt handling, fixedVolpeon2022-12-194-23/+25
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* Avoid increased VRAM usage on validationVolpeon2022-12-154-12/+29
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* More generic datset filterVolpeon2022-12-145-13/+25
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* Unified loading of TI embeddingsVolpeon2022-12-134-65/+54
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* Optimized Textual Inversion training by filtering dataset by existence of ↵Volpeon2022-12-133-10/+47
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* Fixed sample/checkpoint frequencyVolpeon2022-12-132-14/+10
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* Add support for resume in Textual InversionVolpeon2022-12-134-111/+101
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* Dreambooth: Support loading Textual Inversion embeddingsVolpeon2022-12-124-31/+57
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* Remove embedding checkpoints from Dreambooth trainingVolpeon2022-12-111-40/+16
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* Package updatesVolpeon2022-12-111-3/+3
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* Training improvements such as tag dropoutVolpeon2022-12-112-36/+68
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* Support attention_mask of text encoderVolpeon2022-12-104-15/+29
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* Various updated; shuffle prompt content during trainingVolpeon2022-12-103-18/+48
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* Fix sample stepsVolpeon2022-12-062-2/+2
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* UpdateVolpeon2022-12-044-18/+15
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* UpdateVolpeon2022-12-012-6/+6
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* UpdateVolpeon2022-12-014-13/+16
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* UpdateVolpeon2022-12-014-19/+23
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* UpdateVolpeon2022-11-302-12/+34
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* Adjusted training to upstreamVolpeon2022-11-282-50/+56
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* Fixed noise calculation for v-predictionVolpeon2022-11-282-13/+37
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* Fixed and improved Textual Inversion trainingVolpeon2022-11-271-44/+68
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* FixVolpeon2022-11-272-2/+0
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* Generic loading of scheduler (training)Volpeon2022-11-272-34/+18
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* Make prompt processor compatible with any modelVolpeon2022-11-271-1/+2
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