Instructions to use fogside/sksrpm-test-run with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fogside/sksrpm-test-run with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fogside/sksrpm-test-run", dtype=torch.bfloat16, device_map="cuda") prompt = "3d render of sksrpm" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from fogside/sksrpm-test-run: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/fogside/sksrpm-test-run/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://fogside/sksrpm-test-run/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/fogside/sksrpm-test-run/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 07ce9b5a4b8a3bd325a127577dbbe998113be160c67d5a71f15635a581efc033
- Size of remote file:
- 492 MB
- SHA256:
- bfd4c4f88cdc0d605d5dae3fd473189acf87edf7491cd75cd2bae4b73b988585
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