yasserrmd/Text2SQL-1.5B
TEXT GENERATIONConcurrency Cost:1Published On:Mar 6, 2025License:apache-2.0Open Weights Warm

yasserrmd/Text2SQL-1.5B is a 1.5 billion parameter Qwen2-based natural language to SQL model developed by yasserrmd. Fine-tuned from unsloth/qwen2.5-coder-1.5b-instruct-bnb-4bit, it excels at converting user queries into structured SQL statements, supporting complex multi-table queries with high accuracy. This model is optimized for text-to-SQL conversion, providing both the SQL code and an explanation, and has a context length of 131072 tokens.

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Parameters:1.5BContext length:32kArchitecture:TransformerPrecision:BF16Quantized variants:Available
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yasserrmd/Text2SQL-1.5B
Popular Sampler Settings

Most commonly used values from Featherless users

temperature

This setting influences the sampling randomness. Lower values make the model more deterministic; higher values introduce randomness. Zero is greedy sampling.

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top_p

This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.

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top_k

This limits the number of top tokens to consider. Set to -1 to consider all tokens.

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frequency_penalty

This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.

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presence_penalty

This setting penalizes new tokens based on their presence in the generated text so far. Values > 0 encourage new tokens; < 0 encourages repetition.

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repetition_penalty

This setting penalizes new tokens based on their appearance in the prompt and generated text. Values > 1 encourage new tokens; < 1 encourages repetition.

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min_p

This setting representing the minimum probability for a token to be considered relative to the most likely token. Must be in [0, 1]. Set to 0 to disable.

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