Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use digiplay/Opiate_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use digiplay/Opiate_v3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("digiplay/Opiate_v3", 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 digiplay/Opiate_v3: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/digiplay/Opiate_v3/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://digiplay/Opiate_v3@refs/pr/2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/digiplay/Opiate_v3/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 919732891f324a2cac585e21811a3728c6525816b07c483c0c9fc119b9b67df6
- Size of remote file:
- 492 MB
- SHA256:
- 8c1045d44c6af28ff0e6d2746e9d06c28f591e3769c1a6d0ccacce3fe1b722f4
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