Instructions to use harsh8001/explode101 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use harsh8001/explode101 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("harsh8001/explode101") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 2d0faca7583cf9831de7a8612338a34f4bf16a363c2cc3476084b8b70b5c188d
- Size of remote file:
- 27.2 MB
- SHA256:
- 1f1fb5df4c548f9774758403e8bccb7c10e679a16f73a8d062a9f86a58b47b56
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