paper-qa vs transformers
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| paper-qa | transformers | |
|---|---|---|
| Tagline | High accuracy RAG for answering questions from scientific documents with citations | 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models |
| Stars | 8.8k | 162k |
| Forks | 887 | 34k |
| Open issues | 140 | 2.5k |
| Language | Python | Python |
| License | Apache-2.0 | Apache-2.0 |
| Last pushed | Jun 29, 2026 | Jul 7, 2026 |
| Categories | LLM Frameworks, Data & Retrieval | Data & Retrieval, Model Training, LLM Frameworks |
paper-qa
PaperQA2 is a Python package designed to perform retrieval augmented generation (RAG) on various document types, focusing specifically on the scientific literature. It aims to achieve superhuman performance in scientific tasks such as question answering, summarization, and contradiction detection.
Python
transformers
Repo hosts a Python library and framework for NLP, text, audio, vision, multimodal AI model creation, training and inference using PyTorch.
Python