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🔥🔥🔥 Introducing WizardLM-2!
🔥🔥🔥 Introducing WizardLM-2!
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📙Release Blog: 
📙Release Blog: 
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https://wizardlm.github.io/WizardLM2
https://wizardlm.github.io/WizardLM2
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✅Model Weights: 
✅Model Weights: 
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https://huggingface.co/collections/microsoft/wizardlm-661d403f71e6c8257dbd598a
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microsoft/wizardlm-661d403f71e6c8257dbd598a
https://huggingface.co/collections/microsoft/wizardlm-661d403f71e6c8257dbd598a
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🐦Twitter: 
🐦Twitter: 
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https://twitter.com/WizardLM_AI/status/1779899325868589372
https://twitter.com/WizardLM_AI/status/1779899325868589372
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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.
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.
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WizardLM-2 8x22B is our most advanced model, and the best opensource LLM in our internal evaluation on highly complex tasks. 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.
WizardLM-2 8x22B is our most advanced model, and the best opensource LLM in our internal evaluation on highly complex tasks. 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.
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🤗 WizardLM 2 Capacities:
🤗 WizardLM 2 Capacities:
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1. MT-Bench (Figure-1)
1. MT-Bench (Figure-1)
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The WizardLM-2 8x22B even demonstrates highly competitive performance compared to the most advanced proprietary works such as GPT-4-Trubo and Glaude-3. 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.
The WizardLM-2 8x22B even demonstrates highly competitive performance compared to the most advanced proprietary works such as GPT-4-Trubo and Glaude-3. 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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2. Human Preferences Evaluation (Figure 2)
2. Human Preferences Evaluation (Figure 2)
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Through this human preferences evaluation, WizardLM-2's capabilities are very close to the cutting-edge proprietary models such as GPT-4-1106-preview, and significantly ahead of all the other open source models.
Through this human preferences evaluation, WizardLM-2's capabilities are very close to the cutting-edge proprietary models such as GPT-4-1106-preview, and significantly ahead of all the other open source models.
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🔍Method Overview:
🔍Method Overview:
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As the natural world's human-generated data becomes increasingly exhausted through LLM training, we believe that: the data carefully created by AI and the model step-by-step supervised by AI will be the sole path towards more powerful AI.
As the natural world's human-generated data becomes increasingly exhausted through LLM training, we believe that: the data carefully created by AI and the model step-by-step supervised by AI will be the sole path towards more powerful AI.
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In the past one year, we built a fully AI powered synthetic training system. (As shown in the Figure 3). 
In the past one year, we built a fully AI powered synthetic training system. (As shown in the Figure 3). 
🔥🔥🔥 Introducing WizardLM-2!

📙Release Blog: https://wizardlm.github.io/WizardLM2
✅Model Weights: https://huggingface.co/collections/microsoft/wizardlm-661d403f71e6c8257dbd598a 
🐦Twitter: https://twitter.com/WizardLM_AI/status/1779899325868589372

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, and the best opensource LLM in our internal evaluation on highly complex tasks. 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.

🤗 WizardLM 2 Capacities:

1. MT-Bench (Figure-1)
The WizardLM-2 8x22B even demonstrates highly competitive performance compared to the most advanced proprietary works such as GPT-4-Trubo and Glaude-3. 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.

2. Human Preferences Evaluation (Figure 2)
Through this human preferences evaluation, WizardLM-2's capabilities are very close to the cutting-edge proprietary models such as GPT-4-1106-preview, and significantly ahead of all the other open source models.

🔍Method Overview:
As the natural world's human-generated data becomes increasingly exhausted through LLM training, we believe that: the data carefully created by AI and the model step-by-step supervised by AI will be the sole path towards more powerful AI.

In the past one year, we built a fully AI powered synthetic training system. (As shown in the Figure 3). 
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WizardLM tangmen victor vaclavkosar s0me-0ne oceansweep Bruno xianbao haipeng1 syslot Lin-Rexter Chaklam JosMax veeragoni CocoSun ChuckMcSneed osanseviero julien-c Ramikan-BR niclaslindqvist radames taher30 jinkazamapro07 m-ric jayjay5230 Jaward latent-variable jameshwade Revs64 JSCPPProgrammer cppowboy ShaneTian jlzhou alesthehuman bardusco-tau mahirzukic2 noobmaster29 Emigmo KvrParaskevi Aressions
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sparkycollier haipeng1 Lin-Rexter YueJie osanseviero julien-c ragibhasan radames latent-variable sugatoray alesthehuman mahirzukic2 noobmaster29
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KyleLyu djester alesthehuman pharmaia noobmaster29 tobitege StudentWen VDBLOI2024
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