Text-to-Image
Diffusers
Chinese
AltDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
bilingual
Chinese
en
English
Instructions to use BAAI/AltDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BAAI/AltDiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BAAI/AltDiffusion", 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
- Draw Things
- DiffusionBee
| __pycache__ | |
| .idea/ | |
| logs/ | |
| test_tokenizer.py | |
| samples_text2image/ | |
| generate_contexts/ | |
| venv/ | |
| *__pycache__ | |
| .DS_Store | |
| .vscode | |
| *.swo | |
| *.swp | |
| *log | |
| build | |
| dist | |
| eazybigmodel.egg-info | |
| flagai.egg-info | |
| test_report | |
| /data/ | |
| /tests/*/data | |
| checkpoints | |
| state_dict | |
| checkpoints* | |
| vocabs | |
| tensorboard* | |
| datasets | |
| qqp | |
| glm_large_qqp_pytorch |