Soybean ControlNet Sd15 v1
This pipeline was finetuned from stable-diffusion-v1-5/stable-diffusion-v1-5 on the ButterChicken98/soybean-disease-controlnet dataset. Below are some example images generated with the finetuned pipeline using the...
Model source
- Kind
- Other
- File size
- 1.13 GB
- Base model
- stable-diffusion-v1-5/stable-diffusion-v1-5
- Version
- vmodel
- Updated
- Oct 8, 2026
- Downloads
- 3
- Source
- Hugging Face
Source description
Text-to-image finetuning - ButterChicken98/soybean_controlnet_sd15_v1
This pipeline was finetuned from stable-diffusion-v1-5/stable-diffusion-v1-5 on the ButterChicken98/soybean-disease-controlnet dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['A soybean leaf with early symptoms of Aerial Blight, showing small water-soaked spots at the leaf tip.']:
val_imgs_grid
Pipeline usage
You can use the pipeline like so:
from diffusers import DiffusionPipeline
import torch
pipeline = DiffusionPipeline.from_pretrained("ButterChicken98/soybean_controlnet_sd15_v1", torch_dtype=torch.float16)
prompt = "A soybean leaf with early symptoms of Aerial Blight, showing small water-soaked spots at the leaf tip."
image = pipeline(prompt).images[0]
image.save("my_image.png")
Training info
These are the key hyperparameters used during training:
- Epochs: 115
- Learning rate: 5e-05
- Batch size: 8
- Gradient accumulation steps: 1
- Image resolution: 512
- Mixed-precision: None
More information on all the CLI arguments and the environment are available on your wandb run page.
Intended uses & limitations
How to use
# TODO: add an example code snippet for running this diffusion pipeline
Limitations and bias
[TODO: provide examples of latent issues and potential remediations]
Training details
[TODO: describe the data used to train the model]
Sources
1 source
Sources
1 sourceVerified Oct 8
Model artifacts
1 artifact
Model artifacts
1 artifactsafety_checker/model.safetensors
safetensors · 1.13 GB · SHA-256 fb351a5ded81…fde8 · Hugging Face
Download fileSource excerpts
3 excerpts
Source excerpts
3 excerpts--- base_model: stable-diffusion-v1-5/stable-diffusion-v1-5 library_name: diffusers license: creativeml-openrail-m inference: true tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - diffusers-training --- <!-- This model card has been generated automatically according to the information the training script had access to. You should probably proofread and complete it, then remove this comment. --> # Text-to-image finetuning - ButterChicken98/soybean_controlnet_sd15_v1 This pipeline was finetuned from **stable-diffusion-v1-5/stable-diffusion-v1-5** on the **ButterChicken98/soybean-disease-controlnet** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['A soybean leaf with early symptoms of Aerial Blight, showing small water-soaked spots at the leaf tip.']:  ## Pipeline usage You can use the pipeline like so: ```python from diffusers import DiffusionPipeline import torch pipeline = DiffusionPipeline.from_pretrained("ButterChicken98/soybean_controlnet_sd15_v1", torch_dtype=torch.float16) prompt = "A soybean leaf with early symptoms of Aerial Blight, showing small water-soaked spots at the leaf tip." image = pipeline(prompt).images[0] image.save("my_image.png") ``` ## Training info These are the key hyperparameters used during training: * Epochs: 115 * Learning rate: 5e-05 * Batch size: 8 * Gradient accumulation steps: 1 * Image resolution: 512 * Mixed-precision: None More information on all the CLI arguments and the environment are available on your [`wandb` run page](https://wandb.ai/butterchicken-iit-indore/text2image-fine-tune/runs/dd5fnkki). ## Intended uses & limitations #### How to use ```python # TODO: add an example code snippet for running this diffusion pipeline ``` #### Limitations and bias [TODO: provide examples of latent issues and potential remediations] ## Training details [TODO: describe the data used to train the model]
Source context: 3 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo ButterChicken98/soybean_controlnet_sd15_v1
Source context: 1 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo ButterChicken98/soybean_controlnet_sd15_v1
