Instructions to use sh20raj/Genivis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sh20raj/Genivis with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sh20raj/Genivis", 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
| import torch | |
| from diffusers import FluxPipeline | |
| pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16) | |
| pipe.enable_model_cpu_offload() #save some VRAM by offloading the model to CPU. Remove this if you have enough GPU power | |
| prompt = "A cat holding a sign that says hello world" | |
| image = pipe( | |
| prompt, | |
| height=1024, | |
| width=1024, | |
| guidance_scale=3.5, | |
| num_inference_steps=50, | |
| max_sequence_length=512, | |
| generator=torch.Generator("cpu").manual_seed(0) | |
| ).images[0] | |
| image.save("flux-dev.png") |