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:
- 1672db12f572bc6a531a715f099344f72f0b921d948c593ac097649246728482
- Size of remote file:
- 29.9 MB
- SHA256:
- 67cc20c53c36938eb367a000338ac39726710351a2656dad3a4284588f5faf78
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