# Structured Data Processing

A reinforced reasoning model based on the Llama-3.2-3B-Instruct architecture, excelling in mathematical analysis, logical reasoning, and structured data comprehension.

A high-performance mathematical reasoning and general knowledge processing model distilled from Qwen2.5-72B through reinforcement learning, excelling in mathematical reasoning and general knowledge tasks.

A table classification model based on the Apache-2.0 license, supporting the English language, primarily used for table data classification tasks.

A table classification model for the field of biology, capable of accurately classifying biology-related tabular data.

The 70-billion-parameter version of the Llama 3 Groq tool-use model, specifically designed for advanced tool usage and function calling tasks.

TabuLa-8B is a foundational model for table data prediction (classification and binned regression), built on Meta Llama 3.

ProTrix is a model designed for table and sentence contextual planning and reasoning, focusing on joint reasoning tasks involving tabular and textual data.

ReasTAP is a pre-trained model for table reasoning, which injects table reasoning skills through synthetic reasoning examples and is fine-tuned on the WikiTableQuestions dataset

TAPEX is a table pre-training model that learns via neural SQL executor, based on the BART architecture, specifically designed for table reasoning tasks.

TAPEX is a model that learns table reasoning capabilities through neural SQL executor training.

This model is based on the tapas-base architecture, optimized for table input through pre-training, enhancing reasoning capabilities for QA tasks.