Instructions to use AiresPucrs/embedding-model-16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use AiresPucrs/embedding-model-16 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://AiresPucrs/embedding-model-16") - Notebooks
- Google Colab
- Kaggle
Rename english_embedding_vocabulary_16.keras to embedding-model-16.keras
Browse files
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@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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english_embedding_vocabulary_16.keras filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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english_embedding_vocabulary_16.keras filter=lfs diff=lfs merge=lfs -text
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embedding-model-16.keras filter=lfs diff=lfs merge=lfs -text
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english_embedding_vocabulary_16.keras → embedding-model-16.keras
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File without changes
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