Text-to-Image
Diffusers
Trained with AutoTrain
stable-diffusion-xl
stable-diffusion-xl-diffusers
lora
template:sd-lora
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("stablediffusionapi/my-stablediffusion-lora-2265")
prompt = "photo of De bruyne men"
image = pipe(prompt).images[0]ModelsLab LoRA DreamBooth Training - stablediffusionapi/my-stablediffusion-lora-2265
Model description
These are stablediffusionapi/my-stablediffusion-lora-2265 LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were trained using Modelslab. LoRA for the text encoder was enabled: False. Special VAE used for training: None.
Use it with the 🧨 diffusers library
!pip install -q transformers accelerate peft diffusers
from diffusers import DiffusionPipeline
import torch
pipe_id = "stabilityai/stable-diffusion-xl-base-1.0"
pipe = DiffusionPipeline.from_pretrained(pipe_id, torch_dtype=torch.float16).to("cuda")
pipe.load_lora_weights("stablediffusionapi/my-stablediffusion-lora-2265", weight_name="pytorch_lora_weights.safetensors", adapter_name="abc")
prompt = "abc of a hacker with a hoodie"
lora_scale = 0.9
image = pipe(
prompt,
num_inference_steps=30,
cross_attention_kwargs={"scale": lora_scale},
generator=torch.manual_seed(0)
).images[0]
image
Trigger words
You should use photo of De bruyne men to trigger the image generation.
Download model
Weights for this model are available in Safetensors format. Download them in the Files & versions tab.
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Base model
stabilityai/stable-diffusion-xl-base-1.0