Instructions to use vaishnavia40/stack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vaishnavia40/stack with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("vaishnavia40/stack", 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
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Download README.md from vaishnavia40/stack: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
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https://huggingface.co/vaishnavia40/stack/resolve/main/README.md
- Command line
-
hf download hf://vaishnavia40/stack/README.md
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curl -L -o README.md https://huggingface.co/vaishnavia40/stack/resolve/main/README.md
4.73 kB
metadata
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
stack Dreambooth model trained by vaishnavia40 with TheLastBen's fast-DreamBooth notebook
Test the concept via A1111 Colab fast-Colab-A1111
Sample pictures of this concept:

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