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README.md

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+---
+license: llama2
+---
+
+<h3 align="center">
+Xwin-LM: Powerful, Stable, and Reproducible LLM Alignment
+</h3>
+
+<p align="center">
+  <a href="https://huggingface.co/Xwin-LM">
+    <img src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Models-blue">
+  </a>
+</p>
+
+
+
+**Step up your LLM alignment with Xwin-LM!**
+
+Xwin-LM aims to develop and open-source alignment technologies for large language models, including supervised fine-tuning (SFT), reward models, reject sampling, reinforcement learning, etc. Our first release, built-upon on the Llama2 base models, ranked **TOP-1** on [AlpacaEval](https://tatsu-lab.github.io/alpaca_eval/). Notably, it's **the first to surpass GPT-4** on this benchmark. The project will be continuously updated.
+
+## News
+
+- :boom: [Sep, 2023] We released [Xwin-LM-70B-V0.1](https://huggingface.co/Xwin-LM/Xwin-LM-70B-V0.1), which has achieved a win-rate against Davinci-003 of **95.57%** on [AlpacaEval](https://tatsu-lab.github.io/alpaca_eval/) benchmark, ranking as **TOP-1** on AlpacaEval. **It was the FIRST model surpassing GPT-4** on [AlpacaEval](https://tatsu-lab.github.io/alpaca_eval/). Also note its winrate v.s. GPT-4 is **60.61**.
+- :boom: [Sep, 2023] We released [Xwin-LM-13B-V0.1](https://huggingface.co/Xwin-LM/Xwin-LM-13B-V0.1), which has achieved **91.76%** win-rate on [AlpacaEval](https://tatsu-lab.github.io/alpaca_eval/), ranking as **top-1** among all 13B models.
+- :boom: [Sep, 2023] We released [Xwin-LM-7B-V0.1](https://huggingface.co/Xwin-LM/Xwin-LM-7B-V0.1), which has achieved **87.82%** win-rate on [AlpacaEval](https://tatsu-lab.github.io/alpaca_eval/), ranking as **top-1** among all 7B models.
+
+
+## Model Card
+| Model        | Checkpoint | Report | License  |
+|------------|------------|-------------|------------------|
+|Xwin-LM-7B-V0.1| 🤗 <a href="https://huggingface.co/Xwin-LM/Xwin-LM-7B-V0.1" target="_blank">HF Link</a> | 📃**Coming soon (Stay tuned)** | <a href="https://ai.meta.com/resources/models-and-libraries/llama-downloads/" target="_blank">Llama 2 License|
+|Xwin-LM-13B-V0.1| 🤗 <a href="https://huggingface.co/Xwin-LM/Xwin-LM-13B-V0.1" target="_blank">HF Link</a> |  |  <a href="https://ai.meta.com/resources/models-and-libraries/llama-downloads/" target="_blank">Llama 2 License|
+|Xwin-LM-70B-V0.1| 🤗 <a href="https://huggingface.co/Xwin-LM/Xwin-LM-70B-V0.1" target="_blank">HF Link</a> |  |  <a href="https://ai.meta.com/resources/models-and-libraries/llama-downloads/" target="_blank">Llama 2 License|
+## Benchmarks
+
+### Xwin-LM performance on [AlpacaEval](https://tatsu-lab.github.io/alpaca_eval/).
+
+The table below displays the performance of Xwin-LM on [AlpacaEval](https://tatsu-lab.github.io/alpaca_eval/), where evaluates its win-rate against Text-Davinci-003 across 805 questions. To provide a comprehensive evaluation, we present, for the first time, the win-rate against ChatGPT and GPT-4 as well. Our Xwin-LM model family establish a new state-of-the-art performance across all metrics. Notably, Xwin-LM-70B-V0.1 has eclipsed GPT-4 for the first time, achieving an impressive win-rate of **95.57%** to Text-Davinci-003 and **60.61%** to GPT-4.
+
+| **Model**                         | **AlpacaEval (winrate %)** | **AlpacaEval (winrate %)**  |**AlpacaEval (winrate %)** |
+|----------------------------------|------------|----------|-------------|
+|    | **v.s. Text-Davinci-003** | **v.s. ChatGPT** | **v.s. GPT4**|
+| **Xwin-LM-70B-V0.1**                   | **95.57**      | **87.50**          | **60.61**            |
+| GPT-4                          | 95.28  | 84.66     |  50.00      |
+| WizardLM-70B-V1.0           | 92.91  | 80.19     |  46.70      |
+| Llama-2-70B-Chat         | 92.66  | 81.97     |  51.19      |
+| **Xwin-LM-13B-V0.1**          | **91.76**  | **81.79**  |  **55.30**    |
+| ChatGPT                    | 89.37  | 50.00     |  16.60      |
+| WizardLM-13B-V1.2         | 89.17  | 75.75     |  41.91      |
+| **Xwin-LM-7B-V0.1**      | **87.35** | **76.40**    |  **47.57**     |
+| Llama-2-13B-Chat     | 81.09  | 64.22     |  30.92      |
+
+##

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