Instructions to use issai/Beynele with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use issai/Beynele with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("issai/Beynele", 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 Settings
- Draw Things
- DiffusionBee
Update Beynele model card license wording
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README.md
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license:
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language:
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This repository is a private pre-release staging repository. Access and license
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terms will be finalized after paper submission.
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## Use With Diffusers
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```python
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## Licensing
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## Citation
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license: apache-2.0
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language:
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## Use With Diffusers
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```python
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## Licensing
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Beynele is released under the Apache License 2.0. The model is adapted from
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`Alpha-VLLM/Lumina-Image-2.0`; users should also follow the licenses and terms
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of any bundled or upstream components used by the Diffusers pipeline.
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## Citation
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