Text-to-Image
Diffusers
TensorBoard
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use ashnrk/textual_inversion_annual_crop_te with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ashnrk/textual_inversion_annual_crop_te with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ashnrk/textual_inversion_annual_crop_te", dtype=torch.bfloat16, device_map="cuda") prompt = "a centered satellite photo of <annual-crop> annual crop land." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
DreamBooth - ashnrk/textual_inversion_annual_crop_te
This is a dreambooth model derived from runwayml/stable-diffusion-v1-5. The weights were trained on a centered satellite photo of annual crop land. using DreamBooth. You can find some example images in the following.
DreamBooth for the text encoder was enabled: True.
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Model tree for ashnrk/textual_inversion_annual_crop_te
Base model
runwayml/stable-diffusion-v1-5