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I am working on training a model, but since I have not finalized my dataset, I am progressively adding small chunks of images and captions once every few days. However, so far, I have always deleted all the cached image latents and text embeddings and recreated new ones when I started to train a new model. My dataset could be as follows:
The dataset is getting huge and it takes >2 days to do the caching. So I am trying to find a way to reuse the encoded latent and embeddings from data_0 to data_2 when I add new data, data_x, to the dataset. Is this somehow doable by the available features in SimpleTuner? Thanks in advance!
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I am working on training a model, but since I have not finalized my dataset, I am progressively adding small chunks of images and captions once every few days. However, so far, I have always deleted all the cached image latents and text embeddings and recreated new ones when I started to train a new model. My dataset could be as follows:
The dataset is getting huge and it takes >2 days to do the caching. So I am trying to find a way to reuse the encoded latent and embeddings from
data_0
todata_2
when I add new data,data_x
, to the dataset. Is this somehow doable by the available features in SimpleTuner? Thanks in advance!Beta Was this translation helpful? Give feedback.
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