Text-to-Image
Diffusers
ONNX
Safetensors
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StableDiffusionXLPipeline
common-canvas
stable-diffusion
sdxl
Instructions to use common-canvas/CommonCanvas-XL-C with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use common-canvas/CommonCanvas-XL-C with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("common-canvas/CommonCanvas-XL-C", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Is there instructions for finetuning this model?
#4
by NunyaBuzor - opened
Is there instructions for finetuning this model? or does it work the same way as stable diffusion?
This CommonCanvas model doesn't really provide any instructions on finetuning it. It's a shame because it would make the model very useful.
It should work just like fine-tuning SDXL! You can try the same scripts and the same logic and it should work out of the box! Try and give feedback :)
NunyaBuzor changed discussion status to closed
I will also be adding instructions shortly for how to do it with our MosaicML/diffusion codebase. Stay tuned!
I will also be adding instructions shortly for how to do it with our MosaicML/diffusion codebase. Stay tuned!
any update on this?