Instructions to use vedaco/Tera.v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use vedaco/Tera.v3 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://vedaco/Tera.v3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 70522404a7098a7309f8e84f4ba4a4cae8b3bbf404876e2673f03580dba24e7c
- Size of remote file:
- 4.26 MB
- SHA256:
- 0f7d4efa24327595011ac81c3f84488a92c8985b6ffcba0f9de70d660c3b10b9
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