diffusers
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š¤ Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
I'm currently experimenting with the dreambooth training script, and while the results are very impressive, I think it is missing the super resolution fine tuning phase? In the dreambooth paper...
- Corrects example usage (see #1114 , thanks @socathie !) - Adds example inputs and results
Unborked PR of #1209 > The current example uses Tensorboard as the only available logger. Adding Weights and Biases allows us to interact with the model metrics, alongside the saved...
WIP. The upscaler model does not predict the noise, but the denoised image. Therefore it needs to use schedulers that support `predict_epsilon=False`. In addition, [the noise schedule is configured from...
### Describe the bug `trained_betas` is a numpy array, and it cannot be serialized to JSON. This makes it currently impossible to save the configuration of a custom scheduler that...
**Is your feature request related to a problem? Please describe.** Iām looking for ways to speed the process and save memory **Describe the solution you'd like** I wondered if it...
### Describe the bug I am trying to load diffusers either from a remote. Remote huggingface diffusers is not accessible after a successful login ### Reproduction ```shell (pytorch)$ huggingface-cli login...
**Is your feature request related to a problem? Please describe.** A clear and concise description of what the problem is. Ex. I'm always frustrated when [...] Provide a way to...
Hello, I'm trying to replicate imagen using the diffusers library, so far I've trained the 64x64 unet, next I have to train the 256x256 model. My question is, what is...
Without duplicating the sigmas and timesteps (reference: #1336) ā No duplication of sigmas and timesteps. Does not require ugly function `index_for_timestep` (or confusing oneliner repeated twice in the code) ā...