Instructions to use brendanm1234/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use brendanm1234/output with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("brendanm1234/output", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a <new1> cat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- 1686108428.4355912
- 1686108428.4376051
- 1686108627.3632188
- 1686108627.3655388
- 1686108972.1392918
- 1686108972.1429622
- 1686110149.9877326
- 1686110149.9909382
- 1686110207.2763877
- 1686110207.2780912
- 1686110415.3124232
- 1686110415.3145387
- 88 Bytes xet
- 88 Bytes xet
- 20.8 kB xet
- 88 Bytes xet
- 88 Bytes xet
- 2.14 kB xet