Instructions to use keras-sd/text-encoder-tflite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use keras-sd/text-encoder-tflite 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-sd/text-encoder-tflite") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bb800502b3b5388dcf33eb6e5211bea49f0f1fbdec295cd52ddbe2b237e1c5a2
- Size of remote file:
- 127 MB
- SHA256:
- d0768692a1c233086fcdd4216b5aacd61acac1edbaf4bf5e6c5d862644de52d8
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