Instructions to use rajkumaralma/clay_art with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rajkumaralma/clay_art 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_art") 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 Art

- 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
Clay Art
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_art
Base model
stabilityai/stable-diffusion-xl-base-1.0