Instructions to use Croscot/carritos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Croscot/carritos with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Croscot/carritos", 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
Download checkpoint-5000/optimizer.bin from Croscot/carritos: direct link, hf CLI and curl.
- Browser
- Download file 910 MB
-
https://huggingface.co/Croscot/carritos/resolve/main/checkpoint-5000/optimizer.bin
- Command line
-
hf download hf://Croscot/carritos/checkpoint-5000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/Croscot/carritos/resolve/main/checkpoint-5000/optimizer.bin
910 MB
- Xet hash:
- cc34ae7217b1d28085902947063f25c50ff4821d9b7d59ed7a862f62373ec1ad
- Size of remote file:
- 910 MB
- SHA256:
- 04a1d60f8948ec7715fdbc8c1d3fd082a3c875c7a0b4594b6306efcb6c7b6075
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