Instructions to use Akashegs/sd-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Akashegs/sd-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Akashegs/sd-model", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of sks akashdeep" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from Akashegs/sd-model: direct link, hf CLI and curl.
- Browser
- Download file 235 Bytes
-
https://huggingface.co/Akashegs/sd-model/resolve/main/README.md
- Command line
-
hf download hf://Akashegs/sd-model/README.md
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curl -L -o README.md https://huggingface.co/Akashegs/sd-model/resolve/main/README.md
235 Bytes
metadata
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: photo of sks akashdeep
tags:
- text-to-image
- diffusers
- autotrain
inference: true
DreamBooth trained by AutoTrain
Text encoder was not trained.