Instructions to use microsoft/Lens-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use microsoft/Lens-Turbo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("microsoft/Lens-Turbo", 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
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README.md
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# Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models
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<img src="assets/teaser.
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---
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license: mit
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language:
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- en
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pipeline_tag: text-to-image
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---
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# Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models
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<img src="assets/teaser.webp" alt="Lens Teaser" width="100%" />
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