Instructions to use YellowAstronaut/bEchTle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YellowAstronaut/bEchTle with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("YellowAstronaut/bEchTle") prompt = "A confident young woman with naturally curly blond hair, smiling authentically, standing in a bright, modern office with acoustic wall panels and visible concrete and large windows, wearing a timeless, minimal light beige knit sweater and high-waisted taupe trousers with a simple brown leather belt, no flashy accessories, natural look, high-key natural daylight, soft and airy atmosphere with gentle warm highlights and harmonious, desaturated colors, shallow depth of field with subtle monitor and desk details in the foreground, clear composition with foreground, middle ground, and background, optimistic and approachable mood, editorial corporate photography in the style of the Audi brand guide, photorealistic, cinematic --ar 2:3 --exp 20 --quality 2 --raw --v 7 Job ID: ad947796-4234-45e7-a05a-26cbef26c3a2" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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