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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ ---
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+
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+
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+
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+ <p style="font-size:20px;" align="center">
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+ 🏠 <a href="https://wizardlm.github.io/WizardLM2" target="_blank">WizardLM-2 Release Blog</a> </p>
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+ <p align="center">
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+ 🤗 <a href="https://huggingface.co/collections/microsoft/wizardlm-2-661d403f71e6c8257dbd598a" target="_blank">HF Repo</a> •🐱 <a href="https://github.com/victorsungo/WizardLM/tree/main/WizardLM-2" target="_blank">Github Repo</a> • 🐦 <a href="https://twitter.com/WizardLM_AI" target="_blank">Twitter</a> • 📃 <a href="https://arxiv.org/abs/2304.12244" target="_blank">[WizardLM]</a> • 📃 <a href="https://arxiv.org/abs/2306.08568" target="_blank">[WizardCoder]</a> • 📃 <a href="https://arxiv.org/abs/2308.09583" target="_blank">[WizardMath]</a> <br>
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+ </p>
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+ <p align="center">
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+ 👋 Join our <a href="https://discord.gg/VZjjHtWrKs" target="_blank">Discord</a>
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+ </p>
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+
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+ ## See [here](https://huggingface.co/lucyknada/microsoft_WizardLM-2-7B) for the WizardLM-2-7B re-upload.
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+
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+ ## News 🔥🔥🔥 [2024/04/15]
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+
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+ We introduce and opensource WizardLM-2, our next generation state-of-the-art large language models,
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+ which have improved performance on complex chat, multilingual, reasoning and agent.
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+ New family includes three cutting-edge models: WizardLM-2 8x22B, WizardLM-2 70B, and WizardLM-2 7B.
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+
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+ - WizardLM-2 8x22B is our most advanced model, demonstrates highly competitive performance compared to those leading proprietary works
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+ and consistently outperforms all the existing state-of-the-art opensource models.
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+ - WizardLM-2 70B reaches top-tier reasoning capabilities and is the first choice in the same size.
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+ - WizardLM-2 7B is the fastest and achieves comparable performance with existing 10x larger opensource leading models.
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+
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+ For more details of WizardLM-2 please read our [release blog post](https://web.archive.org/web/20240415221214/https://wizardlm.github.io/WizardLM2/) and upcoming paper.
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+
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+
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+ ## Model Details
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+
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+ * **Model name**: WizardLM-2 8x22B
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+ * **Developed by**: WizardLM@Microsoft AI
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+ * **Model type**: Mixture of Experts (MoE)
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+ * **Base model**: [mistral-community/Mixtral-8x22B-v0.1](https://huggingface.co/mistral-community/Mixtral-8x22B-v0.1)
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+ * **Parameters**: 141B
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+ * **Language(s)**: Multilingual
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+ * **Blog**: [Introducing WizardLM-2](https://web.archive.org/web/20240415221214/https://wizardlm.github.io/WizardLM2/)
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+ * **Repository**: [https://github.com/nlpxucan/WizardLM](https://github.com/nlpxucan/WizardLM)
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+ * **Paper**: WizardLM-2 (Upcoming)
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+ * **License**: Apache2.0
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+
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+
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+ ## Model Capacities
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+
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+
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+ **MT-Bench**
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+
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+ We also adopt the automatic MT-Bench evaluation framework based on GPT-4 proposed by lmsys to assess the performance of models.
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+ The WizardLM-2 8x22B even demonstrates highly competitive performance compared to the most advanced proprietary models.
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+ Meanwhile, WizardLM-2 7B and WizardLM-2 70B are all the top-performing models among the other leading baselines at 7B to 70B model scales.
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+
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+ <p align="center" width="100%">
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+ <a ><img src="https://web.archive.org/web/20240415175608im_/https://wizardlm.github.io/WizardLM2/static/images/mtbench.png" alt="MTBench" style="width: 96%; min-width: 300px; display: block; margin: auto;"></a>
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+ </p>
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+
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+
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+ **Human Preferences Evaluation**
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+
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+ We carefully collected a complex and challenging set consisting of real-world instructions, which includes main requirements of humanity, such as writing, coding, math, reasoning, agent, and multilingual.
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+ We report the win:loss rate without tie:
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+
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+ - WizardLM-2 8x22B is just slightly falling behind GPT-4-1106-preview, and significantly stronger than Command R Plus and GPT4-0314.
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+ - WizardLM-2 70B is better than GPT4-0613, Mistral-Large, and Qwen1.5-72B-Chat.
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+ - WizardLM-2 7B is comparable with Qwen1.5-32B-Chat, and surpasses Qwen1.5-14B-Chat and Starling-LM-7B-beta.
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+
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+ <p align="center" width="100%">
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+ <a ><img src="https://web.archive.org/web/20240415163303im_/https://wizardlm.github.io/WizardLM2/static/images/winall.png" alt="Win" style="width: 96%; min-width: 300px; display: block; margin: auto;"></a>
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+ </p>
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+
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+
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+
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+
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+
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+ ## Method Overview
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+ We built a **fully AI powered synthetic training system** to train WizardLM-2 models, please refer to our [blog](https://web.archive.org/web/20240415221214/https://wizardlm.github.io/WizardLM2/) for more details of this system.
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+
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+ <p align="center" width="100%">
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+ <a ><img src="https://web.archive.org/web/20240415163303im_/https://wizardlm.github.io/WizardLM2/static/images/exp_1.png" alt="Method" style="width: 96%; min-width: 300px; display: block; margin: auto;"></a>
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+ </p>
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+
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+
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+
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+
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+
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+ ## Usage
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+
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+ ❗<b>Note for model system prompts usage:</b>
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+
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+
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+ <b>WizardLM-2</b> adopts the prompt format from <b>Vicuna</b> and supports **multi-turn** conversation. The prompt should be as following:
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+
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+ ```
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+ A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful,
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+ detailed, and polite answers to the user's questions. USER: Hi ASSISTANT: Hello.</s>
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+ USER: Who are you? ASSISTANT: I am WizardLM.</s>......
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+ ```
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+
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+ <b> Inference WizardLM-2 Demo Script</b>
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+
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+ We provide a WizardLM-2 inference demo [code](https://github.com/nlpxucan/WizardLM/tree/main/demo) on our github.
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