Comments (1)
Yep, this just looks like what you can get right now. Both the initial decoder and the upsampler are undertrained and undersized. You'll see better results if you come back in a month or so.
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Related Issues (20)
- What pretraining datasets do you use? HOT 1
- support ddim sampling? HOT 1
- Cuda:1 doesnt work HOT 1
- Run on cpu HOT 2
- Error has occurred in google colab notebook HOT 3
- Colab Notebook Error: KeyError: 'decoder_path' HOT 1
- Train DALL-E2 on my own dataset HOT 1
- about pre-trained models HOT 1
- gradio_inference: DuplicateBlockError HOT 2
- example_inference produces noise HOT 4
- How to finetune with the pretrained model? HOT 2
- Inpainting using pretrained models
- RuntimeError: mat1 and mat2 shapes cannot be multiplied (1x10 and 768x1280) HOT 2
- HW Requirements for running example_inference.py HOT 1
- Error message after install HOT 3
- RuntimeError: "addmm_impl_cpu_" not implemented for 'Half'
- bad results when generating images with inference code
- How to combine the huggingface pretrained models with you repository?
- No configs on Huggingface
- bad results when generating images with inference code HOT 1
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