Instructions to use BilalHasan/Sentiment-Analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use BilalHasan/Sentiment-Analysis with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://BilalHasan/Sentiment-Analysis") - Notebooks
- Google Colab
- Kaggle
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Download README.md from BilalHasan/Sentiment-Analysis: direct link, hf CLI and curl.
- Browser
- Download file 481 Bytes
-
https://huggingface.co/BilalHasan/Sentiment-Analysis/resolve/main/README.md
- Command line
-
hf download hf://BilalHasan/Sentiment-Analysis/README.md
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curl -L -o README.md https://huggingface.co/BilalHasan/Sentiment-Analysis/resolve/main/README.md
481 Bytes
| license: apache-2.0 | |
| language: | |
| - en | |
| pipeline_tag: text-classification | |
| --- | |
| # About | |
| This model performs sentiment analysis on an input text. The model outputs one of the two classes: Positive or Negative | |
| # Setup instructions | |
| 1. Clone the repository: | |
| ```bash | |
| git clone https://github.com/Bilal303-ai/Sentiment-Analysis | |
| cd Sentiment-Analysis | |
| ``` | |
| 3. Install `tensorflow` and `keras_nlp` | |
| 5. Run the following command: | |
| ```bash | |
| python inference.py | |
| ``` |