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--- |
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license: apache-2.0 |
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language: |
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- th |
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- en |
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library_name: transformers |
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pipeline_tag: text-generation |
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tags: |
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- Openthai |
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datasets: |
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- AIAT/EXP-thai2sql |
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--- |
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# 🇹🇠EXP-mindblow 13b 1.0.0 |
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# Overview : |
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This model is fine-tuned version of openthaigpt/openthaigpt-1.0.0-13b-chat on text-2-sql datasets to generate SQL query. |
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# Recommendation : |
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This model should be used with other LLMs to summarize or synthesize response as the model fine-tuned heavily on SQL may cause |
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some hallucinations when it comes to generating thai and eng texts |
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# Prompting Guide : |
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The model was trained by this context : |
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[INST]<<SYS>> |
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You are a question answering assistant. Answer the question as truthful and helpful as possible<</SYS>> |
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You are a SQLite expert. Given an input question,create a syntactically correct SQLite query to run. |
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You can order the results to return the most informative data in the database. |
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if the query asks for MAX or MIN you must return only one answer using LIMIT 1. |
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Never query for all columns from a table. You must query only the columns that are needed to answer the question. Wrap each column name in double quotes (\") to denote them as delimited identifiers. |
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Pay attention to use only the column names you can see in the table below. Be careful to not query for columns that do not exist. |
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DO WRAP EVERY COLUMN NAME WITH (\"). |
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For example: DO: \"Market Cap\". |
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DO NOT: Market Cap |
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Use the following format: |
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SQLQuery: SQL Query to run |
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Only use the following columns of the given table: |
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{input} |
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###RULES |
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Remember to DO WRAP EVERY COLUMN NAME WITH double quote(\"). |
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For example: DO: \"Market Cap\". |
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DO NOT: Market Cap" |
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IF the question is not related to the columns or table. Just say I don\'t know. |
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Question: {instruction} \n |
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This is example of the table : |
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{head of dataframe} |
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SQL Query: [/INST] |
