Instructions to use WALIDALI/pillartripoli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WALIDALI/pillartripoli with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WALIDALI/pillartripoli", 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
Download text_encoder/pytorch_model.bin from WALIDALI/pillartripoli: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/WALIDALI/pillartripoli/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://WALIDALI/pillartripoli/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/WALIDALI/pillartripoli/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 50051531cbc695ac8ea1efeb705c23f0e3c40095dc01e4b2a940140e0060ea63
- Size of remote file:
- 246 MB
- SHA256:
- 84b80603e13532cd3b003637b8d65086277c0d7de384938feeb46af59ac198ad
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