Text-to-Image
Diffusers
TensorBoard
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use Vernon-2/output_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Vernon-2/output_test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Vernon-2/output_test", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-100/optimizer.bin from Vernon-2/output_test: direct link, hf CLI and curl.
- Browser
- Download file 6.88 GB
-
https://huggingface.co/Vernon-2/output_test/resolve/main/checkpoint-100/optimizer.bin
- Command line
-
hf download hf://Vernon-2/output_test/checkpoint-100/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/Vernon-2/output_test/resolve/main/checkpoint-100/optimizer.bin
6.88 GB
- Xet hash:
- 3698724e58367c38fc54f1e9eaa059f707f0315af6d982da05aa64a01a143550
- Size of remote file:
- 6.88 GB
- SHA256:
- 7619174b9a49e5c0d7bfda7b4eef89267fce62a2a0e306eadd275ae3eb0afed8
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