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-200/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-200/optimizer.bin
- Command line
-
hf download hf://Vernon-2/output_test/checkpoint-200/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/Vernon-2/output_test/resolve/main/checkpoint-200/optimizer.bin
6.88 GB
- Xet hash:
- 481831c492d657cd122bdaa756775dabc48bb8f03debaa4e691e54a07b493bd5
- Size of remote file:
- 6.88 GB
- SHA256:
- a32cffb454f97825015ff132fccdfbae03ca21d21f7eca4bda3f367624a9e4d3
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