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
Download checkpoint-500/pytorch_model.bin from anshudaur/cat_model_small_lr: direct link, hf CLI and curl.
- Browser
- Download file 76.7 MB
-
https://huggingface.co/anshudaur/cat_model_small_lr/resolve/main/checkpoint-500/pytorch_model.bin
- Command line
-
hf download hf://anshudaur/cat_model_small_lr/checkpoint-500/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/anshudaur/cat_model_small_lr/resolve/main/checkpoint-500/pytorch_model.bin
76.7 MB
- Xet hash:
- 84279c2fd1ee162ad7ecdcdb2f9d555dc9260662b16b4619f7f7bbe227b8a3b7
- Size of remote file:
- 76.7 MB
- SHA256:
- 7f4e2c03b700b502a86652abd7575502334ef64a2a6a26000745c3f0299c06b7
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