Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
food
Instructions to use veereshd/Berlinberger-berger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use veereshd/Berlinberger-berger with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("veereshd/Berlinberger-berger", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of Berlinberger berger in the city" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from veereshd/Berlinberger-berger: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/veereshd/Berlinberger-berger/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://veereshd/Berlinberger-berger/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/veereshd/Berlinberger-berger/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- da997c56ab66e6004c4a0df6185a04d97986de9d2266124a198e8be8ba50c25c
- Size of remote file:
- 492 MB
- SHA256:
- a20d724dacc3f94e73753462567b578a6395b725e17b4ddaeddf0dd3bc148729
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