Instructions to use molinamarc/syntheva with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use molinamarc/syntheva with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("molinamarc/syntheva", 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
Ctrl+K
This model has 7 files scanned as unsafe.
- DiT
- MUSIQ
- RadImageNet_models
- SSCN
- autoencoders_kl
- contrastive
- ffhq
- ldm
- metrics
- resshift
- sd-vae-ft-mse
- stylegan2
- stylegan3
- vae
- vqgan
- 1.73 kB
- 28.4 MB xet
- 95.7 MB xet
- 94.5 MB xet
- 1.82 GB xet
- 141 MB xet
- 244 MB xet
- 244 MB xet
- 95.7 MB xet
- 354 MB xet
- 201 MB xet
- 32.3 MB xet
- 109 MB xet
- 1.25 GB xet
- 46.8 MB xet
- 46.8 MB xet
- 103 MB xet
- 537 MB xet
- 575 MB xet