Instructions to use MasterShomya/Tweets_Sentiment_Analyzer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use MasterShomya/Tweets_Sentiment_Analyzer with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://MasterShomya/Tweets_Sentiment_Analyzer") - Notebooks
- Google Colab
- Kaggle
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pipeline_tag: text-classification
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tags:
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- sentiment-analysis
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- keras
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- lstm
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- attention
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---
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# Sentiment Analysis from Scratch (LSTM + Attention)
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This model performs sentiment analysis on short texts or tweets. Built completely from scratch with a Bidirectional LSTM and an Attention mechanism, it predicts whether the input is **Positive** or **Negative**, along with a confidence score.
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✅ Try it out below using the widget!
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