Text-to-Image
Diffusers
OpenVINO
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
openvino-export
Instructions to use rac2026/tiny-sd-openvino with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rac2026/tiny-sd-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("rac2026/tiny-sd-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 Settings
- Draw Things
- DiffusionBee
| license: creativeml-openrail-m | |
| base_model: segmind/tiny-sd | |
| datasets: | |
| - recastai/LAION-art-EN-improved-captions | |
| tags: | |
| - stable-diffusion | |
| - stable-diffusion-diffusers | |
| - text-to-image | |
| - diffusers | |
| - openvino | |
| - openvino-export | |
| inference: true | |
| pipeline_tag: text-to-image | |
| This model was converted to OpenVINO from [`segmind/tiny-sd`](https://huggingface.co/segmind/tiny-sd) using [optimum-intel](https://github.com/huggingface/optimum-intel) | |
| via the [export](https://huggingface.co/spaces/echarlaix/openvino-export) space. | |
| First make sure you have optimum-intel installed: | |
| ```bash | |
| pip install optimum[openvino] | |
| ``` | |
| To load your model you can do as follows: | |
| ```python | |
| from optimum.intel import OVDiffusionPipeline | |
| model_id = "rac2026/tiny-sd-openvino" | |
| model = OVDiffusionPipeline.from_pretrained(model_id) | |
| ``` | |