Instructions to use kwangjin/novel_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kwangjin/novel_lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("kwangjin/novel_lora") prompt = "a photo of sks person" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
YAML Metadata Error:"base_model" with value "../../../diffusers_ckpts/anythingv3/" is not valid. Use a model id from https://hf.co/models.
LoRA DreamBooth - kwangjin/novel_lora
These are LoRA adaption weights for ../../../diffusers_ckpts/anythingv3/. The weights were trained on a photo of sks person using DreamBooth. You can find some example images in the following.
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