Instructions to use rashxyz/ariv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rashxyz/ariv2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("rashxyz/ariv2", dtype=torch.bfloat16, device_map="cuda") prompt = "A high tech solarpunk utopia in the Amazon rainforest" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from rashxyz/ariv2: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/rashxyz/ariv2/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://rashxyz/ariv2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rashxyz/ariv2/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 9706131902726171468f4035f77ef359860955aee727363a1a0b52155fc0dd3a
- Size of remote file:
- 246 MB
- SHA256:
- a7b11ada06b3729e27b9fdb6b1cb296f0bdb2d9093e12ca08104012c1748cfad
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