Instructions to use openbmb/VisCPM-Paint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use openbmb/VisCPM-Paint with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("openbmb/VisCPM-Paint", 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
Commit History
update ckpt b8b90d5
pyx9913 commited on
Rename pipeline_stable_diffusion.py to pipeline.py 3fbf51c
Rename viscpm_paint_balance_checkpoint.pt to pytorch_model.balance.bin 628dca4
Rename viscpm_paint_zhplus_checkpoint.pt to pytorch_model.bin 62883b8
feat: 🎸 add paint model code 4d32fc1
pyx9913 commited on