| | --- |
| | base_model: ButterChicken98/dec_logs_ymv_v4_balanced |
| | library_name: diffusers |
| | license: creativeml-openrail-m |
| | inference: true |
| | tags: |
| | - stable-diffusion |
| | - stable-diffusion-diffusers |
| | - text-to-image |
| | - diffusers |
| | - controlnet |
| | - 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. --> |
| |
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| |
|
| | # controlnet-ButterChicken98/soy_ymv_depth_controlnet_v1 |
| |
|
| | These are controlnet weights trained on ButterChicken98/dec_logs_ymv_v4_balanced with new type of conditioning. |
| | You can find some example images below. |
| |
|
| | prompt: A soybean leaf with faint yellow mosaic patterns and minor curling, indicating early signs of Yellow Mosaic Virus. |
| |  |
| |
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| |
|
| | ## 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] |
