Instructions to use dataautogpt3/ProteusV0.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dataautogpt3/ProteusV0.2 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/ProteusV0.2", dtype=torch.bfloat16, device_map="cuda") prompt = "black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from dataautogpt3/ProteusV0.2: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/dataautogpt3/ProteusV0.2/resolve/refs%2Fpr%2F6/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://dataautogpt3/ProteusV0.2@refs/pr/6/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dataautogpt3/ProteusV0.2/resolve/refs%2Fpr%2F6/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 6c5a51310c94aaed232342c8b093e379e3c374c181bb6d971a4944943d96fe39
- Size of remote file:
- 492 MB
- SHA256:
- 1ddfca21f06dd593ae65ce9814404ad7c4139c884552e686c4ab70a6e09c7005
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.