Instructions to use jeffreykthomas/sd-model-finetuned-lora-affectnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jeffreykthomas/sd-model-finetuned-lora-affectnet with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jeffreykthomas/sd-model-finetuned-lora-affectnet") prompt = "A picture of an older woman with a sad expression" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Stable Diffusion v1 Finetuned on Affectnet

- Prompt
- A picture of an older woman with a sad expression
Model description
Fine Tuned on AffectNet dataset
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for jeffreykthomas/sd-model-finetuned-lora-affectnet
Base model
CompVis/stable-diffusion-v1-4