Instructions to use procedure2012/Zephyr-Summarizer-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use procedure2012/Zephyr-Summarizer-3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="procedure2012/Zephyr-Summarizer-3B")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("procedure2012/Zephyr-Summarizer-3B") model = AutoModel.from_pretrained("procedure2012/Zephyr-Summarizer-3B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| library_name: transformers | |
| # Zephyr-Summarizer-3B | |
| <!-- markdownlint-disable first-line-h1 --> | |
| <!-- markdownlint-disable html --> | |
| <!-- markdownlint-disable no-duplicate-header --> | |
| <div align="center"> | |
| <img src="figures/fig1.png" width="60%" alt="Zephyr-Summarizer-3B" /> | |
| </div> | |
| <hr> | |
| <div align="center" style="line-height: 1;"> | |
| <a href="LICENSE" style="margin: 2px;"> | |
| <img alt="License" src="figures/fig2.png" style="display: inline-block; vertical-align: middle;"/> | |
| </a> | |
| </div> | |
| ## 1. Introduction | |
| Zephyr-Summarizer-3B produces faithful, abstractive summaries across documents, dialogues and transcripts. | |
| <p align="center"> | |
| <img width="80%" src="figures/fig3.png"> | |
| </p> | |
| ## 2. Evaluation Results | |
| ### Comprehensive Benchmark Results | |
| <div align="center"> | |
| | | Benchmark | BriefLM | Zephyr-1B | Condenser | Zephyr-Summarizer-3B | | |
| |---|---|---|---|---|---| | |
| | **Core Reasoning Tasks** | Math Reasoning | 0.613 | 0.638 | 0.643 | 0.660 | | |
| | | Logical Reasoning | 0.808 | 0.827 | 0.819 | 0.850 | | |
| | | Common Sense | 0.770 | 0.774 | 0.744 | 0.796 | | |
| | **Language Understanding** | Reading Comprehension | 0.736 | 0.770 | 0.744 | 0.776 | | |
| | | Question Answering | 0.604 | 0.639 | 0.632 | 0.664 | | |
| | | Text Classification | 0.806 | 0.797 | 0.793 | 0.850 | | |
| | | Sentiment Analysis | 0.774 | 0.792 | 0.809 | 0.825 | | |
| | **Generation Tasks** | Code Generation | 0.706 | 0.726 | 0.744 | 0.752 | | |
| | | Creative Writing | 0.699 | 0.703 | 0.677 | 0.726 | | |
| | | Dialogue Generation | 0.676 | 0.690 | 0.671 | 0.720 | | |
| | | Summarization | 0.762 | 0.794 | 0.796 | 0.814 | | |
| | **Specialized Capabilities** | Translation | 0.798 | 0.803 | 0.797 | 0.831 | | |
| | | Knowledge Retrieval | 0.695 | 0.699 | 0.673 | 0.732 | | |
| | | Instruction Following | 0.792 | 0.803 | 0.771 | 0.808 | | |
| | | Safety Evaluation | 0.777 | 0.777 | 0.751 | 0.790 | | |
| </div> | |
| ### Overall Performance Summary | |
| The Zephyr-Summarizer-3B demonstrates strong performance across all evaluated benchmark categories, with particularly notable results in reasoning and generation tasks. | |
| ## 3. Chat Website & API Platform | |
| We offer a chat interface and API for you to interact with Zephyr-Summarizer-3B. Please check our official website for more details. | |
| ## 4. How to Run Locally | |
| Please refer to our code repository for more information about running Zephyr-Summarizer-3B locally. | |
| ### Temperature | |
| We recommend setting the temperature parameter to 0.6. | |
| ## 5. License | |
| This repository is released under the apache-2.0 license. The model supports commercial use. | |
| ## 6. Contact | |
| If you have any questions, please contact us at info@zephyr.works. | |