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 Settings
- Draw Things
- DiffusionBee
Download assets/cat.png from dataautogpt3/FluxteusV1: direct link, hf CLI and curl.
- Browser
- Download file 933 kB
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https://huggingface.co/dataautogpt3/FluxteusV1/resolve/main/assets/cat.png
- Command line
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hf download hf://dataautogpt3/FluxteusV1/assets/cat.png
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curl -L -o cat.png https://huggingface.co/dataautogpt3/FluxteusV1/resolve/main/assets/cat.png
933 kB
