Text-to-Image
Diffusers
OpenVINO
English
OVStableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
art
artistic
anime
dreamshaper
lcm
openvino-export
Instructions to use plane0654/dreamshaper-8-lcm-openvino with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use plane0654/dreamshaper-8-lcm-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("plane0654/dreamshaper-8-lcm-openvino", torch_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
File size: 734 Bytes
167d3b2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | {
"_class_name": "OVStableDiffusionPipeline",
"_diffusers_version": "0.29.1",
"feature_extractor": [
"transformers",
"CLIPFeatureExtractor"
],
"image_encoder": [
null,
null
],
"requires_safety_checker": true,
"safety_checker": [
"stable_diffusion",
"StableDiffusionSafetyChecker"
],
"scheduler": [
"diffusers",
"PNDMScheduler"
],
"text_encoder": [
"optimum",
"OVModelTextEncoder"
],
"text_encoder_2": [
null,
null
],
"tokenizer": [
"transformers",
"CLIPTokenizer"
],
"unet": [
"optimum",
"OVModelUnet"
],
"vae_decoder": [
"optimum",
"OVModelVaeDecoder"
],
"vae_encoder": [
"optimum",
"OVModelVaeEncoder"
]
}
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