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
File size: 297 Bytes
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---
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.
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