Text-to-Image
Diffusers
OpenVINO
OVStableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
openvino-export
Instructions to use ysn-rfd/Sweet-mix_v2.2_flat-openvino with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ysn-rfd/Sweet-mix_v2.2_flat-openvino with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ysn-rfd/Sweet-mix_v2.2_flat-openvino", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
This model was converted to OpenVINO from digiplay/Sweet-mix_v2.2_flat using optimum-intel
via the export space.
First make sure you have optimum-intel installed:
pip install optimum[openvino]
To load your model you can do as follows:
from optimum.intel import OVStableDiffusionPipeline
model_id = "ysn-rfd/Sweet-mix_v2.2_flat-openvino"
model = OVStableDiffusionPipeline.from_pretrained(model_id)
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Model tree for ysn-rfd/Sweet-mix_v2.2_flat-openvino
Base model
digiplay/Sweet-mix_v2.2_flat