Instructions to use Jeswin001/Finetuned_diffusion_interiordesign with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jeswin001/Finetuned_diffusion_interiordesign with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Jeswin001/Finetuned_diffusion_interiordesign") prompt = "Design a modern home office with a large wooden desk facing a window, a comfortable ergonomic chair, and shelves filled with books and decorative items. Include a laptop on the desk, a small indoor plant, and a motivational quote framed on the wall. The color scheme should be calm and professional, with light gray walls and blue accents." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Duplicate from Osama03/Finetuned_diffusion_interiordesign
Browse filesCo-authored-by: Osama Jamal Abd Elmonsef Sleem <Osama03@users.noreply.huggingface.co>
- .gitattributes +35 -0
- README.md +41 -0
- checkpoint-10000/model.safetensors +3 -0
- checkpoint-10000/optimizer.bin +3 -0
- checkpoint-10000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-10000/random_states_0.pkl +3 -0
- checkpoint-10000/scheduler.bin +3 -0
- checkpoint-5000/model.safetensors +3 -0
- checkpoint-5000/optimizer.bin +3 -0
- checkpoint-5000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-5000/random_states_0.pkl +3 -0
- checkpoint-5000/scheduler.bin +3 -0
- images/example_izowsnvkj.png +0 -0
- pytorch_lora_weights.safetensors +3 -0
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README.md
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---
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license: creativeml-openrail-m
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base_model:
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- CompVis/stable-diffusion-v1-4
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tags:
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- diffusion
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- stable_diffusion
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- lora
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- text-to-image
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- room_images_generation
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library_name: diffusers
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widget:
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- text: >-
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Design a modern home office with a large wooden desk facing a window, a
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comfortable ergonomic chair, and shelves filled with books and decorative
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items. Include a laptop on the desk, a small indoor plant, and a
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motivational quote framed on the wall. The color scheme should be calm and
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professional, with light gray walls and blue accents.
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output:
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url: images/example_izowsnvkj.png
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---
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# Room Design Text-to-Image Generator (Fine-Tuned Stable Diffusion v1-4)
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## Model Description
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This model is a fine-tuned version of the CompVis/stable-diffusion-v1-4, trained specifically on a custom dataset of room images using LoRA (Low-Rank Adaptation). This fine-tuning technique allows the model to specialize in generating diverse room layouts, shapes, and designs based on text prompts while maintaining the computational efficiency of the original architecture.
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The LoRA method enables the model to focus on room-specific features and design patterns without the need for extensive retraining or large-scale computational resources. It is ideal for scenarios requiring text-to-image generation that aligns with specific room descriptions.
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## Model Applications
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This model can be used for:
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- Interior design inspiration
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- Visualizing room layouts for real estate
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- Creative room design generation
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- Architectural planning and visualization
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## Model Details
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- Base Model: CompVis/stable-diffusion-v1-4
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- Fine-tuning Method: LoRA (Low-Rank Adaptation)
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- Training Dataset: A curated dataset of diverse room images, covering different room types, styles, and layouts.
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(https://www.kaggle.com/datasets/ossm03/room-dataset-for-stable-diffusion/data)
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pytorch_lora_weights.safetensors
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