Text-to-Image
Diffusers
Safetensors
English
AeroGenPipeline
aerogen
remote-sensing
object-detection
latent-diffusion
bounding-box
Instructions to use BiliSakura/AeroGen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/AeroGen with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BiliSakura/AeroGen", 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/config.json from BiliSakura/AeroGen: direct link, hf CLI and curl.
- Browser
- Download file 137 Bytes
-
https://huggingface.co/BiliSakura/AeroGen/resolve/main/text_encoder/config.json
- Command line
-
hf download hf://BiliSakura/AeroGen/text_encoder/config.json
-
curl -L -o config.json https://huggingface.co/BiliSakura/AeroGen/resolve/main/text_encoder/config.json
137 Bytes
| { | |
| "target": "text_encoder.clip_text_encoder.AeroGenCLIPTextEncoder", | |
| "params": { | |
| "version": "openai/clip-vit-large-patch14" | |
| } | |
| } |