DSPy: The framework for programming—not prompting—foundation models

Table Transformer (TATR) is a deep learning model for extracting tables from unstructured documents (PDFs and images). This is also the official repository for the PubTables-1M dataset and GriTS ev…

An efficient, flexible and full-featured toolkit for fine-tuning LLM (InternLM2, Llama3, Phi3, Qwen, Mistral, ...)

Summarize existing representative LLMs text datasets.

RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.

GoMate：RAG Framework within Reliable input,Trusted output

MedicalGPT: Training Your Own Medical GPT Model with ChatGPT Training Pipeline. 训练医疗大模型，实现了包括增量预训练(PT)、有监督微调(SFT)、RLHF、DPO、ORPO。

A tool for evaluating LLMs

Datasets and Evaluation Scripts for CompHRDoc

HerbiV是一个具有多种功能的中药网络药理学分析工具，可进行经典的网络药理学及反向网络药理学分析。HerbiV is a multi-functional traditional chinese medicine network pharmacology analysis tool for classical network pharmacology and reverse network…

Contrast-agnostic segmentation of MRI scans

The implementation of the technical report: "Customized Segment Anything Model for Medical Image Segmentation"

Medical Image Retrieval

Workflow for Optimal Radiomics Classification

Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks. Support: https://discourse.slicer.org/c/community/radiomics

MRI to predict L-dopa response on PD patients

Pytorch implementation of paper Ladder Fine-tuning approach for SAM integrating complementary network.

Simultaneous Nuclear Instance Segmentation and Classification in H&E Histology Images.

Publicly Available Brain image anaLysis tOol kit

DocLayNet: A Large Human-Annotated Dataset for Document-Layout Analysis

EDS "lite" edition

基于自动乳腺全容积成像（ABVS）影像组学的机器学习模型鉴别BI-RADS 4类病灶良恶性的临床价值

Python code used to calculate radiomics on CT-images of NSCLC patients