Instructions to use ottopilot/WhitneyDelgado with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ottopilot/WhitneyDelgado with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/v1-5-pruned-v6", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ottopilot/WhitneyDelgado") prompt = "RAW photo, candid, medium shot, front view, WhitDel, clothes pull, open blouse, exposed breasts, pencil skirt, thighhighs, office, glasses ,secretary, seductive, sexual <lora:WhitDel:1> <lora:XenoDetailer_v2:0.7>" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
v2.0 upload
Browse filesI completely started over from scratch with a new training set for v2.0.
WhitneyDelgado_v2.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5a91804dbbd2f519b7d15d23a5cf0217f9bcf6d026c6c04428cb65e3beffe883
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size 75620856
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