TabPFN-2.5 is a tabular foundation model based on the Transformer architecture. It utilizes context learning technology and can solve tabular prediction problems in a single forward propagation, providing efficient regression and classification solutions for structured tabular data.

ConTextTab is a deep learning model that combines semantic understanding and context learning, specifically designed to handle tabular data. It processes different data modalities through specialized embedding methods and is trained on large-scale real-world tabular data, performing excellently in multiple benchmark tests, especially setting a new standard in the semantically rich CARTE benchmark test.

SAP RPT 1 OSS is a deep learning model that combines semantic understanding and context learning, specifically designed for tabular data prediction tasks. The model uses specialized embeddings for different data modalities and is trained on large-scale real-world tabular data, performing excellently in a wide range of benchmark tests.

This model is distilled from all-MiniLM-L12-v2, achieving nearly 2x faster inference speed while maintaining high accuracy on both CPU and GPU.

Natural Language ProcessingSafetensorsMultiple Languages

A Transformer-based tabular classification model for financial data analysis

Natural Language ProcessingTransformers

TabPFN is a Transformer-based foundational model for tabular data. Through prior-data-based learning methods, it achieves strong performance on small-scale tabular regression tasks without requiring task-specific training.

TabPFN is a Transformer-based foundational model for tabular data. Through its prior data learning mechanism, it achieves outstanding performance on small-scale tabular datasets without requiring task-specific training.

A multilingual sentiment analysis model fine-tuned based on DistilBERT, supporting 21 languages, suitable for various scenarios such as social media and customer feedback analysis.

Natural Language ProcessingTransformersMultiple Languages

TabPFNMix is a tabular foundation model pretrained on purely synthetic datasets, utilizing an encoder-decoder Transformer architecture, suitable for tabular data regression tasks.

Scientific ComputingSafetensors

A foundational model for tabular data, pretrained on synthetic datasets generated by mixing random classifiers

Scientific ComputingSafetensors

A fine-tuned version of the 5CD-AI/Vintern-1B-v2 multimodal model for Vietnamese document question answering (tabular data)

MultimodalTransformersOther

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

Natural Language ProcessingTensorflow

A sentiment analysis model fine-tuned based on distilbert/distilbert-base-uncased, trained solely on synthetic data, supporting 5 sentiment classifications.

Natural Language ProcessingTransformersEnglish

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

Natural Language ProcessingTransformers

A tabular classification model based on scikit-learn for predicting possible diseases based on symptoms.

Scientific ComputingJoblib

A query-focused table summarization generation model fine-tuned based on the T5-large architecture, specifically designed for converting tabular data into natural language summaries.

Natural Language ProcessingTransformersEnglish

This is a table-to-text model fine-tuned based on BLOOM-560M, specifically designed to convert tabular data into natural language descriptions.

Natural Language ProcessingTransformersEnglish

A tabular data classification model using Gated Residual Network (GRN) and Variable Selection Network (VSN) to predict whether an individual's annual income exceeds $500,000

Scientific ComputingTensorflow

A tabular data classification model based on Transformer architecture, supporting mixed input of numerical and categorical features

Scientific ComputingTensorflow

TAPAS (Table Parser) is a table-based pre-trained language model developed by Google Research, specifically designed for processing tabular data and natural language queries.

Natural Language ProcessingTransformers