Instructions to use dataautogpt3/ProteusV0.3-Lightning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dataautogpt3/ProteusV0.3-Lightning with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dataautogpt3/ProteusV0.3-Lightning", dtype=torch.bfloat16, device_map="cuda") prompt = "Anime Girl holding a sign that says 'Proteus Lighting'" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder_2/pytorch_model.bin from dataautogpt3/ProteusV0.3-Lightning: direct link, hf CLI and curl.
- Browser
- Download file 2.78 GB
-
https://huggingface.co/dataautogpt3/ProteusV0.3-Lightning/resolve/main/text_encoder_2/pytorch_model.bin
- Command line
-
hf download hf://dataautogpt3/ProteusV0.3-Lightning/text_encoder_2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dataautogpt3/ProteusV0.3-Lightning/resolve/main/text_encoder_2/pytorch_model.bin
2.78 GB
- Xet hash:
- 9f7b38fa3fd5870b3e3affc15143aed56ec91fa71cb6abc885398bedfd94c942
- Size of remote file:
- 2.78 GB
- SHA256:
- 221c353f1a2ff937ce09fde8ba528b0d7e7550e1bb95935299b624f2159e11f4
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