ShacharNar/sqlfuse_probgate_tsql_reasoning_prompt_only_answerable_delimeters_eos_8146
Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:3.1BQuant:BF16Ctx Length:32kPublished:Feb 16, 2026Architecture:Transformer Warm

The ShacharNar/sqlfuse_probgate_tsql_reasoning_prompt_only_answerable_delimeters_eos_8146 is a 3.1 billion parameter language model with a 32768 token context length. This model is designed for specific SQL-related reasoning tasks, focusing on T-SQL prompts that require answerable delimiters and end-of-sequence tokens. Its primary strength lies in processing and understanding structured query language contexts, particularly for T-SQL environments.

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Model Overview

The ShacharNar/sqlfuse_probgate_tsql_reasoning_prompt_only_answerable_delimeters_eos_8146 is a 3.1 billion parameter language model with a substantial 32768 token context length. This model is specifically engineered for tasks involving T-SQL reasoning, where the input prompts are structured to include answerable delimiters and end-of-sequence tokens. While specific training details, architecture, and performance benchmarks are not provided in the current model card, its naming convention suggests a specialized focus on SQL-related problem-solving.

Key Characteristics

  • Parameter Count: 3.1 billion parameters.
  • Context Length: Supports a long context window of 32768 tokens.
  • Specialization: Appears to be specialized for T-SQL reasoning tasks.
  • Prompt Structure: Designed to handle prompts with answerable delimiters and end-of-sequence tokens.

Potential Use Cases

Given its apparent specialization, this model could be beneficial for:

  • SQL Query Generation: Assisting in the creation of T-SQL queries based on specific requirements.
  • Database Interaction: Potentially aiding in understanding and responding to T-SQL related prompts.
  • Automated Reasoning: Tasks requiring logical deduction within a T-SQL context, especially where specific delimiters and EOS tokens are crucial for parsing and response generation.