Instructions to use RobinWZQ/CCLAP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RobinWZQ/CCLAP with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("RobinWZQ/CCLAP", 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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This is the
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See also: https://github.com/Robin-WZQ/CCLAP
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# Misuse, Malicious Use, and Out-of-Scope Use
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he model should not be used to intentionally create or disseminate images that create hostile or alienating environments for people. This includes generating images that people would foreseeably find disturbing, distressing, or offensive; or content that propagates historical or current stereotypes.
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This is the pretrained weights for CCLAP (ICME 2023).
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See also: https://github.com/Robin-WZQ/CCLAP
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OR
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Interactive DEMO: https://huggingface.co/spaces/RobinWZQ/CCLAP
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# Misuse, Malicious Use, and Out-of-Scope Use
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he model should not be used to intentionally create or disseminate images that create hostile or alienating environments for people. This includes generating images that people would foreseeably find disturbing, distressing, or offensive; or content that propagates historical or current stereotypes.
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