Bact Puls ControlNet Seg v1
These are controlnet weights trained on ButterChicken98/declogsabv4balanced with new type of conditioning. You can find some example images below.
Model source
- Kind
- ControlNet
- File size
- 1.35 GB
- Base model
- ButterChicken98/dec_logs_ab_v4_balanced
- Version
- vdiffusion_pytorch_model
- Updated
- Oct 27, 2026
- Downloads
- 19
- Source
- Hugging Face
Source description
controlnet-ButterChicken98/bact_puls_controlnet_seg_v1
These are controlnet weights trained on ButterChicken98/dec_logs_ab_v4_balanced with new type of conditioning. You can find some example images below.
prompt: A soybean leaf in early infection of Bacterial Pustule, with tiny raised yellow-brown spots near the edges. images_0)
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 27
Model artifacts
1 artifact
Model artifacts
1 artifactcheckpoint-3000/controlnet/diffusion_pytorch_model.safetensors
safetensors · 1.35 GB · SHA-256 e7f2e3714721…c0b3 · Hugging Face
Download fileSource excerpts
3 excerpts
Source excerpts
3 excerpts--- base_model: ButterChicken98/dec_logs_ab_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. --> # controlnet-ButterChicken98/bact_puls_controlnet_seg_v1 These are controlnet weights trained on ButterChicken98/dec_logs_ab_v4_balanced with new type of conditioning. You can find some example images below. prompt: A soybean leaf in early infection of Bacterial Pustule, with tiny raised yellow-brown spots near the edges.  ## 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: 19 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo ButterChicken98/bact_puls_controlnet_seg_v1
Source context: 10 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo ButterChicken98/bact_puls_controlnet_seg_v1
