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  ## Usage
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  The easiest way to use this model locally is via the [Transformers](https://huggingface.co/docs/transformers/index) library [pipelines for inference](https://huggingface.co/docs/transformers/pipeline_tutorial).
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- Once you have [installed transformers](https://huggingface.co/docs/transformers/installation) you can run the following code. This will download and cache the model locally and allow you to make predictions on text input.
 
 
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  ```
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  from transformers import pipeline
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- classifier = pipeline('text-classification', "davanstrien/autotrain-beyond-the-books")
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  classifier(text)
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  ```
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- This will return predictions in the following format
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  ```
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  [{'label': 'no_jim_crow', 'score': 0.9718555212020874}]
 
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  ## Usage
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  The easiest way to use this model locally is via the [Transformers](https://huggingface.co/docs/transformers/index) library [pipelines for inference](https://huggingface.co/docs/transformers/pipeline_tutorial).
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+
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+ Once you have [installed transformers](https://huggingface.co/docs/transformers/installation), you can run the following code.
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+ This will download and cache the model locally and allow you to make predictions on text input.
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  ```
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  from transformers import pipeline
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+ classifier = pipeline('text-classification', "biglam/autotrain-beyond-the-books")
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  classifier(text)
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  ```
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+ This will return predictions in the following format:
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  ```
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  [{'label': 'no_jim_crow', 'score': 0.9718555212020874}]