Instructions to use ajinkyaT/test-depth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ajinkyaT/test-depth 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("ajinkyaT/test-depth") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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flux1-depth-dev-lora.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:1938b38ea0fdd98080fa3e48beb2bedfbc7ad102d8b65e6614de704a46d8b907
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size 1244440512
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images/test_output.png
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Git LFS Details
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