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@@ -58,7 +58,19 @@ sentiment_analysis = pipeline(
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  ```
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  Our model is also available on AWS! for more information visit [AWS' git](https://github.com/aws-samples/aws-lambda-docker-serverless-inference/tree/main/hebert-sentiment-analysis-inference-docker-lambda)
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  ## Stay tuned!
 
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  ```
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  Our model is also available on AWS! for more information visit [AWS' git](https://github.com/aws-samples/aws-lambda-docker-serverless-inference/tree/main/hebert-sentiment-analysis-inference-docker-lambda)
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+ ### For NER model:
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+ ```
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+ from transformers import pipeline
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+
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+ # how to use?
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+ NER = pipeline(
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+ "token-classification",
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+ model="avichr/heBERT_NER",
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+ tokenizer="avichr/heBERT_NER",
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+ )
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+ NER('讚讜讬讚 诇讜诪讚 讘讗讜谞讬讘专住讬讟讛 讛注讘专讬转 砖讘讬专讜砖诇讬诐')
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+ ```
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  ## Stay tuned!