HuggingFace's Transformers: State-of-the-art Natural Language Processing
About
Recent progress in natural language processing has been driven by advances in both model architecture and model pretraining. Transformer architectures have facilitated building higher-capacity models and pretraining has made it possible to effectively utilize this capacity for a wide variety of tasks. \textit{Transformers} is an open-source library with the goal of opening up these advances to the wider machine learning community. The library consists of carefully engineered state-of-the art Transformer architectures under a unified API. Backing this library is a curated collection of pretrained models made by and available for the community. \textit{Transformers} is designed to be extensible by researchers, simple for practitioners, and fast and robust in industrial deployments. The library is available at \url{https://github.com/huggingface/transformers}.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Mathematical Reasoning | GSM8K | -- | 246 | |
| Instruction Following | Alpaca | -- | 111 | |
| Question Answering | QA | -- | 47 | |
| Text Summarization | CNN/DM | TPS1.27 | 13 | |
| Multilabel Classification | CLIP (test) | Micro F176.7 | 12 | |
| Chat Evaluation | MT-Bench | Throughput (TPS)1.15 | 10 | |
| Code Generation | HumanEval | TPS (Tokens/s)1.15 | 10 | |
| Language Understanding | MMLU-Pro | TPS1.13 | 10 | |
| Dialogue Retrieval | ConvAI2 | R@182.1 | 9 |