Instructions to use valhalla/t2i-depth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use valhalla/t2i-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("valhalla/t2i-depth", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
add model
Browse files- config.json +14 -0
- diffusion_pytorch_model.safetensors +3 -0
config.json
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{
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"_class_name": "T2IAdapter",
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"_diffusers_version": "0.21.0.dev0",
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"adapter_type": "full_adapter_xl",
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"channels": [
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320,
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640,
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1280,
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1280
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],
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"downscale_factor": 16,
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"in_channels": 1,
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"num_res_blocks": 2
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}
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diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:3fefce309fffa67cbaf1480866b11e7d90bc53231bcda2e7572b5497a15173bf
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size 310218544
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