Text-to-Image
Diffusers
TensorBoard
stable-diffusion-xl
stable-diffusion-xl-diffusers
lora
dreambooth
Instructions to use Bharatgwl/sdxl-Bharat-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Bharatgwl/sdxl-Bharat-lora 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("Bharatgwl/sdxl-Bharat-lora") prompt = "a photo of Bharat person" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
SDXL DreamBooth LoRA - sdxl-Bharat-lora
This is a LoRA (Low-Rank Adaptation) model trained with DreamBooth on Stable Diffusion XL.
Trigger Word
Bharat
Usage
from diffusers import StableDiffusionXLPipeline
import torch
pipe = StableDiffusionXLPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
torch_dtype=torch.float16
).to("cuda")
pipe.load_lora_weights("Bharatgwl/sdxl-Bharat-lora")
prompt = "a photo of Bharat person, professional portrait, studio lighting"
image = pipe(prompt, num_inference_steps=30).images[0]
image.save("output.png")
Training Details
- Base Model: stabilityai/stable-diffusion-xl-base-1.0
- Training Steps: 800
- Learning Rate: 0.0001
- Resolution: 1024x1024
- Batch Size: 1
- Instance Prompt: a photo of Bharat person
- Images: 14
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Model tree for Bharatgwl/sdxl-Bharat-lora
Base model
stabilityai/stable-diffusion-xl-base-1.0