Instructions to use dfavenfre/model_use with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use dfavenfre/model_use with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://dfavenfre/model_use") - Notebooks
- Google Colab
- Kaggle
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README.md
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pipeline_tag: text-classification
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tags:
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- finance
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pipeline_tag: text-classification
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- finance
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Model_USE is a pre-trained NLP model to analyze the sentiment of financial or economic commentary, tweet, or news.
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It is built upon Universal Sentence Encoder (USE) and fine-tuned for financial sentiment classification purposes.
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Financial Phrasebank's 'agreeall' dataset was used for fine-tuning.
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