Comments (1)
In the attention module, l_Q, l_K, and l_V are designed to be learnable.
However, since this paper utilizes pretrained models, there is no necessity to train them.
from prompt-to-prompt.
Related Issues (20)
- "TypeError: 'NoneType' object is not callable" upon model.unet() call
- How does this method edit the actions of an object? HOT 1
- PNDMScheduler has no attribute time steps?
- The code doesn't run HOT 1
- support for resolutions lower than 512? HOT 2
- Inconsistency between timestep and noise level in Null-Text Inversion? HOT 1
- Where is the code that visualizes by time step? HOT 1
- Can't load a fine-tuned model due to using an old version of diffusers
- On the non-convergence of null text
- Is training code available? HOT 1
- Does it support SDXL? HOT 2
- When I use Diffusers==0.21.0, p2p seems to generate the same as w/o p2p. Code needs to be upgraded.
- bad results when changing the clothes's color HOT 1
- code for user-defined mask HOT 3
- Can Null text inversion apply to Stable diffusion 2.1? HOT 1
- If I want to add null text inversion to the training process to maintain the feature of the edited image, how can I achieve this?
- code about Delta Denoising Score
- Can we give image as input? HOT 1
- wrong DDIM inversion step HOT 1
- The setting of DDIMScheduler.
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from prompt-to-prompt.