Instructions to use Jinouga/temariv1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jinouga/temariv1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Jinouga/temariv1", 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:
- 47c5723f7b2aa09942fbbb78e3f34d29795a8d0bdfb948b963a05284cc180ab4
- Size of remote file:
- 2.13 GB
- SHA256:
- f232906e6d1767eaf99cf32a9d6a9bf40ad14fec730ffe0845f919e1815c9b1e
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