Instructions to use AiresPucrs/BiLSTM-sentiment-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use AiresPucrs/BiLSTM-sentiment-classifier 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/BiLSTM-sentiment-classifier") - Notebooks
- Google Colab
- Kaggle
Rename tokenizer_senti_model_en.json to tokenizer-BiLSTM-sentiment-classifier.json
Browse files
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senti_model_softmax_en.keras filter=lfs diff=lfs merge=lfs -text
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tokenizer_senti_model_en.json filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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senti_model_softmax_en.keras filter=lfs diff=lfs merge=lfs -text
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tokenizer_senti_model_en.json filter=lfs diff=lfs merge=lfs -text
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tokenizer-BiLSTM-sentiment-classifier.json filter=lfs diff=lfs merge=lfs -text
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tokenizer_senti_model_en.json → tokenizer-BiLSTM-sentiment-classifier.json
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