Diffusers
Safetensors
remote-sensing
computer-vision
diffusion-models
controlnet
generative-model
earth-observation
open-vocabulary
image-dataset
Instructions to use jaychempan/EarthSynth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jaychempan/EarthSynth with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("jaychempan/EarthSynth") pipe = StableDiffusionControlNetPipeline.from_pretrained( "fill-in-base-model", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- f0b906d3f0a9b7c7c743d30fde099c7a0261d6abbb68f093c4db81af07676a6b
- Size of remote file:
- 453 kB
- SHA256:
- e745617e422775a3593f430edec37bb6fbf9bb07cfa5dc1fba62edc704a6a2f8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.