Instructions to use Intel/Ovis-Image-7B-int4-AutoRound with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Intel/Ovis-Image-7B-int4-AutoRound with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Intel/Ovis-Image-7B-int4-AutoRound", 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:
- 2346ed02bc4ef5d17e17184b3ab1fcd2b4860b21072dd2bc82f8794a6547cdb5
- Size of remote file:
- 11.4 MB
- SHA256:
- 33bc7e10f3893cca5d37bdc21b020361cb1ead2b56605f59fdfb0f7c0fe81f3c
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