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README.md

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+---
+license: apache-2.0
+---
+
+
+
+<p style="font-size:20px;" align="center">
+🏠 <a href="https://wizardlm.github.io/WizardLM2" target="_blank">WizardLM-2 Release Blog</a> </p>
+<p align="center">
+🤗 <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>
+</p>
+<p align="center">
+    👋 Join our <a href="https://discord.gg/VZjjHtWrKs" target="_blank">Discord</a>
+</p>
+
+## See [here](https://huggingface.co/lucyknada/microsoft_WizardLM-2-7B) for the WizardLM-2-7B re-upload.
+
+## News 🔥🔥🔥 [2024/04/15]
+
+We introduce and opensource WizardLM-2, our next generation state-of-the-art large language models, 
+which have improved performance on complex chat, multilingual, reasoning and agent. 
+New family includes three cutting-edge models: WizardLM-2 8x22B, WizardLM-2 70B, and WizardLM-2 7B.
+
+- WizardLM-2 8x22B is our most advanced model, demonstrates highly competitive performance compared to those leading proprietary works 
+and consistently outperforms all the existing state-of-the-art opensource models.
+- WizardLM-2 70B reaches top-tier reasoning capabilities and is the first choice in the same size. 
+- WizardLM-2 7B is the fastest and achieves comparable performance with existing 10x larger opensource leading models.
+
+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.
+
+
+## Model Details
+
+* **Model name**: WizardLM-2 8x22B
+* **Developed by**: WizardLM@Microsoft AI
+* **Model type**: Mixture of Experts (MoE)
+* **Base model**: [mistral-community/Mixtral-8x22B-v0.1](https://huggingface.co/mistral-community/Mixtral-8x22B-v0.1)
+* **Parameters**: 141B
+* **Language(s)**: Multilingual
+* **Blog**: [Introducing WizardLM-2](https://web.archive.org/web/20240415221214/https://wizardlm.github.io/WizardLM2/)
+* **Repository**: [https://github.com/nlpxucan/WizardLM](https://github.com/nlpxucan/WizardLM)
+* **Paper**: WizardLM-2 (Upcoming)
+* **License**: Apache2.0
+
+
+## Model Capacities
+
+
+**MT-Bench**
+
+We also adopt the automatic MT-Bench evaluation framework based on GPT-4 proposed by lmsys to assess the performance of models. 
+The WizardLM-2 8x22B even demonstrates highly competitive performance compared to the most advanced proprietary models. 
+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.
+
+<p align="center" width="100%">
+<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>
+</p>
+
+
+**Human Preferences Evaluation**
+
+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. 
+We report the win:loss rate without tie:
+
+- WizardLM-2 8x22B is just slightly falling behind GPT-4-1106-preview, and significantly stronger than Command R Plus and GPT4-0314.
+- WizardLM-2 70B is better than GPT4-0613, Mistral-Large, and Qwen1.5-72B-Chat.
+- WizardLM-2 7B is comparable with Qwen1.5-32B-Chat, and surpasses Qwen1.5-14B-Chat and Starling-LM-7B-beta.
+
+<p align="center" width="100%">
+<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>
+</p>
+
+
+
+
+
+## Method Overview
+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.
+
+<p align="center" width="100%">
+<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>
+</p>
+
+
+
+
+
+## Usage
+
+❗<b>Note for model system prompts usage:</b>
+
+
+<b>WizardLM-2</b>  adopts the prompt format from <b>Vicuna</b> and supports **multi-turn** conversation. The prompt should be as following:
+
+```
+A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, 
+detailed, and polite answers to the user's questions. USER: Hi ASSISTANT: Hello.</s>
+USER: Who are you? ASSISTANT: I am WizardLM.</s>......
+```
+
+<b> Inference WizardLM-2 Demo Script</b>
+
+We provide a WizardLM-2 inference demo [code](https://github.com/nlpxucan/WizardLM/tree/main/demo) on our github.
+
+
+
+

config.json

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+    "architectures": [
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+    "eos_token_id": 2,
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+    "model_type": "mixtral",
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+    "num_hidden_layers": 56,
+    "num_key_value_heads": 8,
+    "num_local_experts": 8,
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+    "rms_norm_eps": 1e-05,
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+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.36.2",
+    "use_cache": false,
+    "vocab_size": 32000,
+    "quantization_config": {
+        "quant_method": "exl2",
+        "version": "0.1.5",
+        "bits": 8.0,
+        "head_bits": 8,
+        "calibration": {
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+            "length": 2048,
+            "dataset": "(default)"
+        }
+    }
+}

generation_config.json

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+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.36.2"
+}

huggingface-metadata.txt

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+branch: main
+download date: 2024-04-15 16:48:15
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+  },
+  "additional_special_tokens": [],
+  "bos_token": "<s>",
+  "chat_template": "{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{{ messages[0]['content'].strip() }}{% else %}{% set loop_messages = messages %}{{ 'A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user\\'s questions.' }}{% endif %}{% for message in loop_messages %}{% if loop.index0 == 0 %}{% if message['role'] == 'system' or message['role'] == 'user' %}{{ ' USER: ' + message['content'].strip() }}{% else %}{{ ' ASSISTANT: ' + message['content'].strip() + eos_token }}{% endif %}{% else %}{% if message['role'] == 'system' or message['role'] == 'user' %}{{ '\nUSER: ' + message['content'].strip() }}{% else %}{{ ' ASSISTANT: ' + message['content'].strip() + eos_token }}{% endif %}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ ' ASSISTANT:' }}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": true,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<unk>",
+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": true
+}