Instructions to use rajkumaralma/clay_animation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rajkumaralma/clay_animation with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("rajkumaralma/clay_animation") prompt = "<lora:Clay Animation:1>Clay Animation - Disappointment to triumph, a 3D image showing a student with a disappointed expression, an eraser erasing the low score, and rewriting it into a high score. The mood transitions from despair to triumph. The environment is a study desk with exam papers and stationery. The lighting draws attention to the erasing and rewriting of the score." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Clay Animation

- Prompt
- <lora:Clay Animation:1>Clay Animation - Disappointment to triumph, a 3D image showing a student with a disappointed expression, an eraser erasing the low score, and rewriting it into a high score. The mood transitions from despair to triumph. The environment is a study desk with exam papers and stationery. The lighting draws attention to the erasing and rewriting of the score.
Model description
rajkumaralma/clay_animation
Trigger words
You should use Clay Animation page to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for rajkumaralma/clay_animation
Base model
stabilityai/stable-diffusion-xl-base-1.0