Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion
stable-diffusion-diffusers
controlnet
Instructions to use hxgrace/model_6_20 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hxgrace/model_6_20 with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("hxgrace/model_6_20") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-2-1-base", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from hxgrace/model_6_20: direct link, hf CLI and curl.
- Browser
- Download file 521 Bytes
-
https://huggingface.co/hxgrace/model_6_20/resolve/main/README.md
- Command line
-
hf download hf://hxgrace/model_6_20/README.md
-
curl -L -o README.md https://huggingface.co/hxgrace/model_6_20/resolve/main/README.md
521 Bytes
metadata
license: creativeml-openrail-m
base_model: stabilityai/stable-diffusion-2-1-base
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- controlnet
inference: true
controlnet-hxgrace/model_6_20
These are controlnet weights trained on stabilityai/stable-diffusion-2-1-base with new type of conditioning, based on the dataset found at hxgrace/augmentedSketches. It was trained with a batch size of 6 over 20 epochs.