Instructions to use anshudaur/cat_model_small_lr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use anshudaur/cat_model_small_lr with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("anshudaur/cat_model_small_lr", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a <new1> cat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 45f77dddc1cacf4f231c106ae2a31d3035f15fabd422a0270925a1c3535db2ee
- Size of remote file:
- 457 MB
- SHA256:
- 57c7e2113df9db32babfe09e644e1587bec80a56e2360c823cf2d12bebae6199
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