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--- |
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language: |
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- en |
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--- |
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# RUN |
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## BERT Language Model |
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```python |
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from transformers import pipeline |
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model_path = "/language-ml-lab/iranian-azerbaijani-nlp/AzerBert/checkpoint-11630" |
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tokenizer_path = "/language-ml-lab/iranian-azerbaijani-nlp/AzerBert" |
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fill_mask = pipeline("fill-mask", model=model_path, tokenizer=tokenizer_path) |
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example = "خارجدن یئمک گتیریلمهسینه امکان وئرمیردیلر [MASK]" |
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arr_example = example.split(" ") |
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result = fill_mask(example, arr_example) |
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for prediction in result: |
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print("Predicted Word: ", prediction["token_str"]) |
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print(f"Final sentence: {prediction['sequence']}, confidence: {prediction['score']}") |
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``` |
