Instructions to use EnD-Diffusers/digital-vivid-memories with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EnD-Diffusers/digital-vivid-memories with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("EnD-Diffusers/digital-vivid-memories", dtype=torch.bfloat16, device_map="cuda") prompt = "anidzk2" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from EnD-Diffusers/digital-vivid-memories: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/EnD-Diffusers/digital-vivid-memories/resolve/refs%2Fpr%2F1/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://EnD-Diffusers/digital-vivid-memories@refs/pr/1/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/EnD-Diffusers/digital-vivid-memories/resolve/refs%2Fpr%2F1/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- ece521276396fd3cb5a9faabd7cc77ccf6a0c91973ed18c7447f249e5668e709
- Size of remote file:
- 492 MB
- SHA256:
- f485b666159df9a2c4ad28affb1006c1e97086e01b1de884826161403474fc12
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