Instructions to use SidXXD/eps_0310-alpha_0200 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/eps_0310-alpha_0200 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SidXXD/eps_0310-alpha_0200", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a <v1*> cat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("SidXXD/eps_0310-alpha_0200", dtype=torch.bfloat16, device_map="cuda")
prompt = "photo of a <v1*> cat"
image = pipe(prompt).images[0]Custom Diffusion - SidXXD/eps_0310-alpha_0200
These are Custom Diffusion adaption weights for stabilityai/stable-diffusion-2-1-base. The weights were trained on photo of a <v1*> cat using Custom Diffusion. You can find some example images in the following.
For more details on the training, please follow this link.
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Model tree for SidXXD/eps_0310-alpha_0200
Base model
stabilityai/stable-diffusion-2-1-base