Instructions to use camenduru/plushies-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use camenduru/plushies-pt with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("camenduru/plushies-pt", 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
| license: openrail | |
| library_name: diffusers | |
| tags: | |
| - TPU | |
| - JAX | |
| - Flax | |
| - stable-diffusion | |
| - text-to-image | |
| language: | |
| - en | |
| thumbnail: https://huggingface.co/camenduru/plushies/resolve/main/samples.jpg | |
| datasets: | |
| - camenduru/plushies | |
| inference: false | |
| Maybe this is the first ever model trained with TPUs and converted to ๐งจ PyTorch ๐๐ | |
| <br/> | |
| Trained with google cloud TPUs. | |
| ``` | |
| Runtime: 3h 26m 44s | |
| Steps: 18000 | |
| Precision: bf16 | |
| Learning Rate: 1e-6 | |
| ``` | |
|  |