Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
wildcard
Instructions to use llhbr/cpg-products-beer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use llhbr/cpg-products-beer with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("llhbr/cpg-products-beer", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of cpg-products beer on a bar" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 70917c6e7a3fa46a1cd79f1a3ceccb0e2e7a52521605b75b4371bc0b4c880e7e
- Size of remote file:
- 492 MB
- SHA256:
- a20d724dacc3f94e73753462567b578a6395b725e17b4ddaeddf0dd3bc148729
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.