Instructions to use Squiddy3/HazelChu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Squiddy3/HazelChu 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("Squiddy3/HazelChu") prompt = "Hazel Chu" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Hazel_Chu-000005.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:c408a6963c53f349f3ed5a59dfe3ab001ea36a4e0045696aa93c632476ab1c60
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size 19258608
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images/Hazel_Chu_e000005_00_20241106202359.jpeg
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Git LFS Details
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