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@@ -50,4 +50,15 @@ from transformers import AutoTokenizer, AutoModelForSequenceClassification
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  tokenizer = AutoTokenizer.from_pretrained("botryan96/GeoBERT_analyzer")
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  model = AutoModelForTokenClassification.from_pretrained("botryan96/GeoBERT_analyzer")
 
 
 
 
 
 
 
 
 
 
 
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  ```
 
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  tokenizer = AutoTokenizer.from_pretrained("botryan96/GeoBERT_analyzer")
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  model = AutoModelForTokenClassification.from_pretrained("botryan96/GeoBERT_analyzer")
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+
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+ #Define the pipeline
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+ from transformers import pipeline
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+ anlyze_machine=pipeline('text-classification',model = model_checkpoint2)
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+
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+ #Define the sentences
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+ sentences = ['the average iron and sulfate concentrations were calculated to be 19 . 6 5 . 2 and 426 182 mg / l , respectively .',
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+ 'She first gained media attention as a friend and stylist of Paris Hilton']
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+
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+ #Deploy the machine
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+ anlyze_machine(sentences)
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  ```