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  ---
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  library_name: transformers
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  license: mit
 
 
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  ---
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  # Inference
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  ```python
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  import time
@@ -11,20 +17,12 @@ from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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  tokenizer = AutoTokenizer.from_pretrained("PiraiAI/fine-tuned-bahasa-melayu-2L")
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  model = AutoModelForSeq2SeqLM.from_pretrained("PiraiAI/fine-tuned-bahasa-melayu-2L")
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-
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  ```
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- ```python
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-
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-
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- - **Developed by:** Pirai AI Team
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- - **Model type:** Sequence-to-Sequence (Seq2Seq) Model
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- - **Language(s) (NLP):** English and Bahasa Melayu
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-
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  ## Uses
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  ### Direct Use
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  This model can be used directly to translate text from English to Bahasa Melayu and vice versa. It is suitable for applications in translation services, bilingual communication tools, and other language processing tasks.
 
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  ---
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  library_name: transformers
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  license: mit
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+ datasets:
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+ - Helsinki-NLP/opus-100
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  ---
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+ - **Developed by:** Pirai AI Team
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+ - **Model type:** Sequence-to-Sequence (Seq2Seq) Model
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+ - **Language(s) (NLP):** English and Bahasa Melayu
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+
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  # Inference
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  ```python
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  import time
 
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  tokenizer = AutoTokenizer.from_pretrained("PiraiAI/fine-tuned-bahasa-melayu-2L")
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  model = AutoModelForSeq2SeqLM.from_pretrained("PiraiAI/fine-tuned-bahasa-melayu-2L")
 
 
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  ```
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  ## Uses
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+
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  ### Direct Use
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  This model can be used directly to translate text from English to Bahasa Melayu and vice versa. It is suitable for applications in translation services, bilingual communication tools, and other language processing tasks.