Instructions to use dfrer/nanasa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dfrer/nanasa 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-2-1-base", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("dfrer/nanasa") prompt = "Man sleeping next to clock" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
nanasa

- Prompt
- Man sleeping next to clock

- Prompt
- Lady death
Model description
Model based on my personal artwork for experimentation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Use it with the 🧨 diffusers library
from diffusers import AutoPipelineForText2Image
import torch
device = "cuda" if torch.cuda.is_available() else "cpu"
pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-2-1-base', torch_dtype=torch.float16).to(device)
pipeline.load_lora_weights('dfrer/nanasa', weight_name='nanasa-000009.safetensors')
image = pipeline('Lady death').images[0]
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
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Model tree for dfrer/nanasa
Base model
stabilityai/stable-diffusion-2-1-base