Instructions to use saishshinde15/SentimentTensor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use saishshinde15/SentimentTensor with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://saishshinde15/SentimentTensor") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a5718b913dcee681500ddd31828e710d1743a2cdc2a292b9fb3cd67ea702b3f4
- Size of remote file:
- 29.9 MB
- SHA256:
- ad5474595c05edd8d3ff4aa18749c0c6accb27f2402ab53c4fc35ff3d0286995
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