Instructions to use zeromodels/depth_anything_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/depth_anything_base with ZeroModels:
# pip install -U zeromodels # ZeroModels is pure Keras 3, so pick a backend: "jax", "torch" or "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" from zeromodels import AutoZModel # AutoZModel reads the repo's model_type and loads the matching class. # For a task head use the matching loader, e.g. AutoZMImageClassify / AutoZMDetect / # AutoZMSemanticSegment / AutoZMTextGenerate (see zeromodels.auto). model = AutoZModel.from_weights("zeromodels/depth_anything_base") - Keras
How to use zeromodels/depth_anything_base with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://zeromodels/depth_anything_base") - Notebooks
- Google Colab
- Kaggle
Upgrade kf_config.json to v2 (nested config + dtype)
Browse files- kf_config.json +30 -26
kf_config.json
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{
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"library_name": "kerasformers",
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"kerasformers_version": "1.
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"model_module": "kerasformers.models.depth_anything_v1",
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"model_class": "DepthAnythingV1DepthEstimation",
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"variant": "depth_anything_base",
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"weights": "model.weights.h5",
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"model_type": "depth_anything",
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"
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}
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{
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"library_name": "kerasformers",
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"kerasformers_version": "1.2.1",
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"model_module": "kerasformers.models.depth_anything_v1",
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"model_class": "DepthAnythingV1DepthEstimation",
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"variant": "depth_anything_base",
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"weights": "model.weights.h5",
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"schema_version": 2,
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"dtype": "float32",
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"model_type": "depth_anything",
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"vision_config": {
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"backbone_dim": 768,
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"backbone_depth": 12,
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"backbone_num_heads": 12,
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"out_indices": [
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],
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"neck_hidden_sizes": [
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96,
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192,
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384,
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768
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],
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"fusion_hidden_size": 128,
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"reassemble_factors": [
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0.5
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],
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"depth_estimation_type": "relative",
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"max_depth": 1.0,
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"image_size": 518
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}
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}
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