Instructions to use IABCD/eduedudiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use IABCD/eduedudiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("IABCD/eduedudiffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
EduEduDiffusion0.2 Dreambooth model trained by nicolasdec for EduEdu
Test the concept via fast-Colab-A1111
Training version 0.2.
Positive Prompts: PROMPT, (eduedu) style, illustration, vector, cartoon lighting
Negatives: bad anatomy, ugly, missing arms, bad proportions, tiling, missing legs, blurry, poorly drawn feet, morbid, cloned face, extra limbs, mutated hands, cropped, disfigured, mutation, deformed, deformed, mutilated, dehydrated, body out of frame, out of frame, disfigured, bad anatomy, poorly drawn face, duplicate, cut off, poorly drawn hands, error, low contrast, signature, extra arms, underexposed, text, extra fingers, overexposed, too many fingers, extra legs, bad art, ugly, extra limbs, beginner, username, fused fingers, amateur, watermark, gross proportions, distorted face, worst quality, jpeg artifacts, low quality, malformed limbs, long neck, lowres, poorly Rendered face, low resolution, low saturation, bad composition, Images cut out at the top, left, right, bottom, deformed body features, poorly rendered hands
- Downloads last month
- 24