Instructions to use Nap/depth_anything_v2_vitg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Nap/depth_anything_v2_vitg with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Nap/depth_anything_v2_vitg", 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 task tag
#1
by merve HF Staff - opened
README.md
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@@ -3,6 +3,7 @@ license: apache-2.0
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base_model:
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- depth-anything/Depth-Anything-V2-Giant
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library_name: diffusers
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---
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Depth Anything V2 Giant - 1.3B params - FP32 - Converted from .pth to .safetensors
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base_model:
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- depth-anything/Depth-Anything-V2-Giant
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library_name: diffusers
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pipeline_tag: depth-estimation
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---
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Depth Anything V2 Giant - 1.3B params - FP32 - Converted from .pth to .safetensors
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