Instructions to use anhnct/Gligen_Text_Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use anhnct/Gligen_Text_Image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("anhnct/Gligen_Text_Image", 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 vae/diffusion_pytorch_model.fp16.bin from anhnct/Gligen_Text_Image: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/anhnct/Gligen_Text_Image/resolve/main/vae/diffusion_pytorch_model.fp16.bin
- Command line
-
hf download hf://anhnct/Gligen_Text_Image/vae/diffusion_pytorch_model.fp16.bin
-
curl -L -o diffusion_pytorch_model.fp16.bin https://huggingface.co/anhnct/Gligen_Text_Image/resolve/main/vae/diffusion_pytorch_model.fp16.bin
167 MB
- Xet hash:
- f17e49491b75c090bb4d30c36d6d63ccbf1cec9dfc12ffa5b16c809fb28df13e
- Size of remote file:
- 167 MB
- SHA256:
- 9a752f69b257151573383a287e53fc11d96fad6a12ce2d9c33b1a4f94bb589ba
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.