Instructions to use eicu/jessy-3500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use eicu/jessy-3500 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("eicu/jessy-3500", dtype=torch.bfloat16, device_map="cuda") prompt = "sks" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from eicu/jessy-3500: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/eicu/jessy-3500/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://eicu/jessy-3500/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/eicu/jessy-3500/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 8d3f9faf154f52f09563e8998527bf796da18dc18e9543c50bd3f287467a7e03
- Size of remote file:
- 492 MB
- SHA256:
- 30219b8278827f8d16e7cd37fe62542458405c18fa9c09e559a0eabace1b0691
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