Instructions to use LTL07/PSEC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LTL07/PSEC with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LTL07/PSEC", 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
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<h2 style="font-size: 32px; margin: 20px 0;">Skill Expansion and Composition in Parameter Space</h2>
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<h4 style="color: #666; margin-bottom: 25px;">International Conference on Learning Representation (ICLR), 2025</h4>
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<a href="https://arxiv.org/abs/2502.05932">
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<a href="https://ltlhuuu.github.io/PSEC/">
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<a href="https://arxiv.org/pdf/2502.05932.pdf">
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๐ฅ Official Implementation
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<h2 style="font-size: 32px; margin: 20px 0;">Skill Expansion and Composition in Parameter Space</h2>
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<h4 style="color: #666; margin-bottom: 25px;">International Conference on Learning Representation (ICLR), 2025</h4>
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<a href="https://arxiv.org/abs/2502.05932">
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<a href="https://ltlhuuu.github.io/PSEC/">
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<a href="https://arxiv.org/pdf/2502.05932.pdf">
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๐ฅ Official Implementation
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<b>PSEC</b> is a novel framework designed to:
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