Instructions to use keras/sam_base_sa1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/sam_base_sa1b with KerasHub:
import keras_hub # Create a ImageSegmenter model task = keras_hub.models.ImageSegmenter.from_preset("hf://keras/sam_base_sa1b")import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/sam_base_sa1b") - Keras
How to use keras/sam_base_sa1b with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://keras/sam_base_sa1b") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- metadata.json +6 -3
metadata.json
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{
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"keras_version": "3.
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"keras_hub_version": "0.
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"parameter_count": 89677388,
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"date_saved": "2024-
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"keras_version": "3.7.0",
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"keras_hub_version": "0.19.0",
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"parameter_count": 89677388,
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"date_saved": "2024-12-21@22:15:04",
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"tasks": [
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"ImageSegmenter"
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]
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}
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