Instructions to use AIML1/AvatarGenration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AIML1/AvatarGenration with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AIML1/AvatarGenration", dtype=torch.bfloat16, device_map="cuda") prompt = "Create a professional photo with blazer for linked in profile having dark background" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from AIML1/AvatarGenration: direct link, hf CLI and curl.
- Browser
- Download file 297 Bytes
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https://huggingface.co/AIML1/AvatarGenration/resolve/main/README.md
- Command line
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hf download hf://AIML1/AvatarGenration/README.md
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curl -L -o README.md https://huggingface.co/AIML1/AvatarGenration/resolve/main/README.md
297 Bytes
| base_model: stabilityai/stable-diffusion-xl-base-1.0 | |
| instance_prompt: Create a professional photo with blazer for linked in profile having dark background | |
| tags: | |
| - text-to-image | |
| - diffusers | |
| - autotrain | |
| inference: true | |
| # DreamBooth trained by AutoTrain | |
| Text encoder was not trained. | |