Instructions to use chickenpete/nova-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use chickenpete/nova-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("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("chickenpete/nova-lora") prompt = "NOVAMODEL" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Add nova-lora.safetensors
Browse files- nova-lora.safetensors +3 -0
nova-lora.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:b7d5bea6c068b6a2bb25692b863946e6a6bd9108f4257f9ef8035de914f7dbe1
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size 89745224
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