ControlNet
These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below.
Fonte do modelo
- Tipo
- ControlNet
- Tamanho do arquivo
- 1,36 GB
- Modelo base
- runwayml/stable-diffusion-v1-5
- Versão
- vdiffusion_pytorch_model
- Atualizado
- 7 de out. de 2026
- Downloads
- 7
- Fonte
- Hugging Face
Descrição da fonte
controlnet-ntaurozzi/controlnet
These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below.
prompt: a micrograph of an allium cepa root tip mitotic cell 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]
Fontes
1 fonte
Fontes
1 fonteVerificado 7 de out.
Artefatos de modelo
1 artefato
Artefatos de modelo
1 artefatocheckpoint-10000/controlnet/diffusion_pytorch_model.safetensors
safetensors · 1,36 GB · SHA-256 dd87c13d1694…36a3 · Hugging Face
Download fileTrechos de fonte
3 trechos
Trechos de fonte
3 trechos--- base_model: runwayml/stable-diffusion-v1-5 library_name: diffusers license: creativeml-openrail-m inference: true tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - controlnet - diffusers-training - 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-ntaurozzi/controlnet These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below. prompt: a micrograph of an allium cepa root tip mitotic cell  ## 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: 7 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo ntaurozzi/controlnet
Source context: 2 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo ntaurozzi/controlnet
