Text-to-Image
Diffusers
Trained with AutoTrain
stable-diffusion-xl
stable-diffusion-xl-diffusers
lora
template:sd-lora
Instructions to use Kvisten/nocco-apple-v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Kvisten/nocco-apple-v5 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("Kvisten/nocco-apple-v5") prompt = "photo of a nocco bcaa energy drink can with the taste of apple" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
AutoTrain SDXL LoRA DreamBooth - Kvisten/nocco-apple-v5
Model description
These are Kvisten/nocco-apple-v5 LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using DreamBooth.
LoRA for the text encoder was enabled: True.
Special VAE used for training: None.
Trigger words
You should use photo of a nocco bcaa energy drink can with the taste of apple 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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Model tree for Kvisten/nocco-apple-v5
Base model
stabilityai/stable-diffusion-xl-base-1.0