Instructions to use akleine/tiny-sd-turbo_q8_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use akleine/tiny-sd-turbo_q8_0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("akleine/tiny-sd-turbo_q8_0", 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
Download model
Quantized to GGUF from https://huggingface.co/cc-nms/tiny-sd-turbo based on https://huggingface.co/stabilityai/sd-turbo
This gguf file is intended for running with sd.cpp . All credits go to: stabilityai, madebyollin, cc-nms. For questions regarding licensing and usage, go to:
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Hardware compatibility
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8-bit
Model tree for akleine/tiny-sd-turbo_q8_0
Base model
stabilityai/sd-turbo