Instructions to use dataautogpt3/FluxteusV1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dataautogpt3/FluxteusV1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dataautogpt3/FluxteusV1", dtype=torch.bfloat16, device_map="cuda") prompt = "cinematic film still of Kodak Motion Picture Film: (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy\n" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Update README.md
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by Moritz2005 - opened
README.md
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instance_prompt: None
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widget:
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- text: >
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An Oscar winning movie for Best Cinematography a woman in a kimono
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standing on a subway train in Japan Kodak Motion Picture Film Style,
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shallow depth of field, vignette, highly detailed, high budget, bokeh,
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cinemascope, moody, epic, gorgeous, film grain, grainy
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output:
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url: assets/train.png
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- text: 1980s anime portrait of a character
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output:
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url: assets/anime.png
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## License
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Please adhere to the licensing terms as described [here](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md).
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instance_prompt: None
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widget:
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- text: >
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Cinematic film still of 18 year old boy in speedos at a big swimming pool
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- text: 1980s anime portrait of a character
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output:
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url: assets/anime.png
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## License
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Please adhere to the licensing terms as described [here](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md).
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