Instructions to use adtyn1345/Image_Generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use adtyn1345/Image_Generator with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("adtyn1345/Image_Generator", 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 adtyn1345/Image_Generator: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/adtyn1345/Image_Generator/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://adtyn1345/Image_Generator/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/adtyn1345/Image_Generator/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 762211583c1d2b025274dd16f70629f2709635ccc9d7487bcd06fba7c8d7847a
- Size of remote file:
- 246 MB
- SHA256:
- b4e0b369638f555abb9292dcfcedb81cee1b60d362d63d48bbdd5d511a0a9124
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.