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* Pipeline: Perlin noise for init imageVolpeon2023-03-047-18/+70
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* Pipeline: Improved initial image generationVolpeon2023-03-041-23/+26
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* Changed init noise algorithmVolpeon2023-03-031-3/+11
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* Removed offset noise from training, added init offset to pipelineVolpeon2023-03-034-68/+41
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* Implemented different noise offsetVolpeon2023-03-036-28/+16
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* Low freq noise with randomized strengthVolpeon2023-03-031-1/+8
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* Better low freq noiseVolpeon2023-03-021-1/+1
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* Changed low freq noiseVolpeon2023-03-011-23/+10
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* UpdateVolpeon2023-03-0110-535/+39
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* Fixed TI normalization orderVolpeon2023-02-213-15/+19
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* FixVolpeon2023-02-211-6/+3
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* Don't rely on Accelerate for gradient accumulationVolpeon2023-02-215-33/+32
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* Embedding normalization: Ignore tensors with grad = 0Volpeon2023-02-217-45/+31
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* UpdateVolpeon2023-02-185-15/+30
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* Added Lion optimizerVolpeon2023-02-177-39/+592
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* Inference script: Better scheduler configVolpeon2023-02-171-19/+37
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* Back to xformersVolpeon2023-02-175-12/+14
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* Remove xformers, switch to Pytorch NightlyVolpeon2023-02-1710-644/+27
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* FixVolpeon2023-02-161-4/+2
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* Integrated WIP UniPC schedulerVolpeon2023-02-166-14/+655
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* UpdateVolpeon2023-02-153-1/+3
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* Improved batch paddingVolpeon2023-02-151-29/+26
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* Better batch fillingVolpeon2023-02-151-3/+6
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* Better batch filling behaviorVolpeon2023-02-151-3/+7
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* Dataset: Repeat data to fill batch to batch_sizeVolpeon2023-02-151-0/+3
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* Made low-freq noise configurableVolpeon2023-02-141-6/+11
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* Better noise generation during training: ↵Volpeon2023-02-131-0/+7
| | | | https://www.crosslabs.org/blog/diffusion-with-offset-noise
* UpdateVolpeon2023-02-1310-65/+73
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* Integrate Self-Attention-Guided (SAG) Stable Diffusion in my custom pipelineVolpeon2023-02-084-17/+164
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* Fixed Lora trainingVolpeon2023-02-084-37/+35
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* Fix Lora memory usageVolpeon2023-02-075-11/+5
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* Add LoraVolpeon2023-02-0710-93/+819
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* Restored LR finderVolpeon2023-01-209-397/+111
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* Move Accelerator preparation into strategyVolpeon2023-01-194-19/+51
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* UpdateVolpeon2023-01-175-22/+25
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* Optimized embedding normalizationVolpeon2023-01-171-5/+2
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* Smaller emb decayVolpeon2023-01-171-1/+1
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* FixVolpeon2023-01-171-4/+5
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* FixVolpeon2023-01-171-1/+0
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* Make embedding decay work like Adam decayVolpeon2023-01-172-21/+9
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* UpdateVolpeon2023-01-174-9/+12
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* UpdateVolpeon2023-01-176-73/+104
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* Training updateVolpeon2023-01-165-16/+25
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* If valid set size is 0, re-use one image from train setVolpeon2023-01-162-6/+2
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* Moved multi-TI code from Dreambooth to TI scriptVolpeon2023-01-164-244/+131
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* More training adjustmentsVolpeon2023-01-166-43/+101
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* Pad dataset if len(items) < batch_sizeVolpeon2023-01-162-20/+23
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* Handle empty validation datasetVolpeon2023-01-166-76/+91
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* Extended Dreambooth: Train TI tokens separatelyVolpeon2023-01-163-71/+84
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* Implemented extended Dreambooth trainingVolpeon2023-01-164-372/+200
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