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:
- e7dcfd6e72a45ba2ef022bbb594b320be6ee1500864c746d581808585f4ed83b
- Size of remote file:
- 4 kB
- SHA256:
- b4aae19fc8e8b45f1f364fbc2eaf785d7d2991e2606d6cb4e90667f58f5ee032
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.