Instructions to use ShreyashDhoot/v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ShreyashDhoot/v3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-inpainting", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ShreyashDhoot/v3") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
Upload README.md with huggingface_hub
Browse files
README.md
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# ShreyashDhoot/v3
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**Last updated:** 2026-05-
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## Model Description
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## Checkpoints
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- `checkpoint--1000`
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- `checkpoint--3000`
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- `checkpoint--4000`
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- `checkpoint--4500`
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- `checkpoint--
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- `checkpoint--500`
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- `checkpoint--5000`
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## Example Eval Outputs
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---
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_Auto-generated by push_to_hf.py_
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