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
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Download README.md from harsh8001/explode101: direct link, hf CLI and curl.
- Browser
- Download file 421 Bytes
-
https://huggingface.co/harsh8001/explode101/resolve/main/README.md
- Command line
-
hf download hf://harsh8001/explode101/README.md
-
curl -L -o README.md https://huggingface.co/harsh8001/explode101/resolve/main/README.md
421 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/ComfyUI_temp_zhjve_00010_.png
text: '-'
base_model: ''
instance_prompt: explode101
license: apache-2.0
explode101

- Prompt
- -
Trigger words
You should use explode101 to trigger the image generation.
Download model
Download them in the Files & versions tab.