Instructions to use kwagh20ite/FLICKR_comp_v_6000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kwagh20ite/FLICKR_comp_v_6000 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kwagh20ite/FLICKR_comp_v_6000", 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
- Xet hash:
- 5aee2acc0965fb08813bb191ca4a42359c4acbd1aca02ece7c659265aed8f49a
- Size of remote file:
- 4 kB
- SHA256:
- 6f61237b66bd724353fcf6b7d44b6f876a789d0f035e25bcd24b60fac46f218d
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