Comments (2)
Your command looks fine.
It's normal that the counters start again from 0, yes. Our checkpoint doesn't store any information about the training step.
Easiest way to verify that the checkpoint is loaded correctly is to just look at the output images during training.
(If it didn't load correctly, your images should look like they did at the start of training).
from textual_inversion.
Ah thanks a lot :)
from textual_inversion.
Related Issues (20)
- cannot edit the image using new prompt HOT 1
- About hyperparameter optimization
- Different init_words have same loss_epoch curve HOT 3
- Cannot obtain the same results as the paper HOT 4
- Train Textual Inversion in alternative models of Stable Diffusion HOT 3
- Error when running Inversion script HOT 6
- Cuda ran out of memory while running main.py
- When will the Perfusion code be available?
- AttributeError: 'NoneType' object has no attribute 'load' HOT 2
- ValueError: The initializer token must be a single token. HOT 4
- A question about picture generation HOT 1
- what are the difference between models in ldm and first_stage_models? HOT 1
- How to set up to achieve the function of the photo in * style of #, one for learning content and one for learning style. HOT 1
- SD with style get bad result
- AttributeError: module 'main' has no attribute 'LearningRateMonitor'
- When I run it, I get the following error, HOT 1
- _pickle.UnpicklingError: invalid load key, '<'. HOT 7
- _pickle.UnpicklingError: invalid load key, '<'. HOT 2
- Request code about downstream tasks HOT 1
- when Release pre-trained embeddings?
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from textual_inversion.