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         @@ -136,11 +136,13 @@ What is the current status of candidate ID 12345?<|im_end|> 
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            <|im_start|>assistant
         
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            <|tool_call_start|>[get_candidate_status(candidate_id="12345")]<|tool_call_end|>Checking the current status of candidate ID 12345.<|im_end|>
         
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            <|im_start|>tool
         
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            <|tool_response_start|>{"candidate_id": "12345", "status": "Interview Scheduled", "position": "Clinical Research Associate", "date": "2023-11-20"}<|tool_response_end|><|im_end|>
         
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            <|im_start|>assistant
         
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            The candidate with ID 12345 is currently in the "Interview Scheduled" stage for the position of Clinical Research Associate, with an interview date set for 2023-11-20.<|im_end|>
         
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            ```
         
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            **Architecture**: Hybrid model with multiplicative gates and short convolutions: 18 double-gated short-range LIV convolution blocks and 6 grouped query attention (GQA) blocks.
         
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            **Pre-training mixture**: Approximately 75% English, 20% multilingual, and 5% code data sourced from the web and licensed materials.
         
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            <|im_start|>assistant
         
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            <|tool_call_start|>[get_candidate_status(candidate_id="12345")]<|tool_call_end|>Checking the current status of candidate ID 12345.<|im_end|>
         
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            <|im_start|>tool
         
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            <|tool_response_start|>[{"candidate_id": "12345", "status": "Interview Scheduled", "position": "Clinical Research Associate", "date": "2023-11-20"}]<|tool_response_end|><|im_end|>
         
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            <|im_start|>assistant
         
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            The candidate with ID 12345 is currently in the "Interview Scheduled" stage for the position of Clinical Research Associate, with an interview date set for 2023-11-20.<|im_end|>
         
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            ```
         
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            You can directly pass tools as JSON schema or Python functions with `.apply_chat_template()` as shown in [this page](https://huggingface.co/docs/transformers/en/chat_extras) to automatically format the system prompt.
         
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            **Architecture**: Hybrid model with multiplicative gates and short convolutions: 18 double-gated short-range LIV convolution blocks and 6 grouped query attention (GQA) blocks.
         
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            **Pre-training mixture**: Approximately 75% English, 20% multilingual, and 5% code data sourced from the web and licensed materials.
         
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