Instructions to use danbrown/testing-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use danbrown/testing-1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("danbrown/testing-1", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from danbrown/testing-1: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/danbrown/testing-1/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://danbrown/testing-1/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/danbrown/testing-1/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 4d9cfd20cae3fa0b59d583739b8d24a04c7b015c67c36a8eeacfa6fee8e3a4e4
- Size of remote file:
- 492 MB
- SHA256:
- 21ce3e5bbffad12528bfab12093524addf0ffddf2e741578c111e3ac10dd78ba
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