Instructions to use opendiffusionai/stablediffusionxl_t5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use opendiffusionai/stablediffusionxl_t5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("opendiffusionai/stablediffusionxl_t5", 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
- Draw Things
- DiffusionBee
Work in progress
The model files are almost identical to our t5sdxl-v0-bf16 model. However it has had its model_config.json adjusted, so that it will work with new code, that will be going into the "community" diffusers pipeline area.
Alternatively, there is now a "demo.py" script that can use diffusers pipeline styles relatively cleanly, AS-IS!
Precision
Note that the unet is, sadly, only bf16 at this time, since we only have 4090s
Usage
You can use it with the sample code in demo.py
Forward notes
Hmm.. in retrospect... perhaps it would be better to use chatpig/t5-v1_1-xl-encoder-gguf instead of the xxl version.
That is natively 2048 dim, so no need for a projection layer.
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