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StructLM-34B

Text Generation
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  **example input**
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  ```
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- [INST] [INST] <<SYS>>\nYou are an AI assistant that specializes in analyzing and reasoning over structured information. You will be given a task, optionally with some structured knowledge input. Your answer must strictly adhere to the output format, if specified.\n<</SYS>>\n\nUse the information in the following table to solve the problem, choose between the choices if they are provided. table:\n\ncol : day | kilometers row 1 : tuesday | 0 row 2 : wednesday | 0 row 3 : thursday | 4 row 4 : friday | 0 row 5 : saturday | 0\n\n\nquestion:\n\nAllie kept track of how many kilometers she walked during the past 5 days. What is the range of the numbers? [/INST] [/INST]
 
 
 
 
 
 
 
 
 
 
 
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  ```
 
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  ## Intended Uses
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  These models are trained for research purposes. They are designed to be proficient in interpreting linearized structured input. Downstream uses can potentially include various applications requiring the interpretation of structured data.
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  **example input**
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  ```
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+ [INST] [INST] <<SYS>>
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+ You are an AI assistant that specializes in analyzing and reasoning over structured information. You will be given a task, optionally with some structured knowledge input. Your answer must strictly adhere to the output format, if specified.
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+ <</SYS>>
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+ Use the information in the following table to solve the problem, choose between the choices if they are provided. table:
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+ col : day | kilometers row 1 : tuesday | 0 row 2 : wednesday | 0 row 3 : thursday | 4 row 4 : friday | 0 row 5 : saturday | 0
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+ question:
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+ Allie kept track of how many kilometers she walked during the past 5 days. What is the range of the numbers? [/INST] [/INST]
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  ```
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+
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  ## Intended Uses
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  These models are trained for research purposes. They are designed to be proficient in interpreting linearized structured input. Downstream uses can potentially include various applications requiring the interpretation of structured data.
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