Instructions to use harsha19/anu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use harsha19/anu 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("harsha19/anu") prompt = "rups" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Upload rupastraight2final.safetensors
Browse files
rupastraight2final.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:9ae5cb105807637b7e5602414f069d9ac8a728f6978c6c312e6c3b8ba80579a6
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size 612746544
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