Build a RAG (Retrieval Augmented Generation) pipeline from scratch and have it all run locally.

REBEL is a seq2seq model that simplifies Relation Extraction (EMNLP 2021).

ResLT: Residual Learning for Long-tailed Recognition (TPAMI 2022)

A knowledge graph RAG app using LangChain and Neo4j.

Fine tune a T5 transformer model using PyTorch & Transformers🤗

PyTorch Implementation of BioBERT

Insightful Tutorials and Papers about Knowledge Graphs

Some custom dataset examples for PyTorch

Learn how to design systems at scale and prepare for system design interviews

RAG example using DSPy, Gradio, FastAPI

Biomedical Named Entity Recognition and Normalization of Diseases, Chemicals and Genenetic entity classes through the use of state-of-the-art models.

A dataset generator/graph modeling demo of Shareholding Breakthrough with Distributed open-source Graph Database: Nebula Graph. 图数据库应用示例、数据集、图建模：股权关系穿透

Code repository for "Prioritizing Repurposable Drugs for SARS-CoV-2 using Deep Learning and Population-based Validation"

Genomic language model predicts protein co-regulation and function

The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval

Infinity is a high-throughput, low-latency REST API for serving text-embeddings, reranking models and clip

GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

PyTorch implementations of Generative Adversarial Networks.

Python toolkit for NCBI metadata (via eutils) and pubmed article text mining -- official primary repo.

Lexical Analyzer in Python

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

A guidance language for controlling large language models.

The TinyLlama project is an open endeavor to pretrain a 1.1B Llama model on 3 trillion tokens.

Official Chainer implementation of GP-GAN: Towards Realistic High-Resolution Image Blending (ACMMM 2019, oral)

Parameter-Efficient Sparsity Crafting From Dense to Mixture-of-Experts for Instruction Tuning on General Tasks

Tuning the Finetuning: An exploration of achieving success with QLoRA

A high-throughput and memory-efficient inference and serving engine for LLMs

Examples for using ONNX Runtime for machine learning inferencing.