| --- |
| license: apache-2.0 |
| model-index: |
| - name: WizardLM-2-8x22B |
| results: |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: IFEval (0-Shot) |
| type: HuggingFaceH4/ifeval |
| args: |
| num_few_shot: 0 |
| metrics: |
| - type: inst_level_strict_acc and prompt_level_strict_acc |
| value: 52.72 |
| name: strict accuracy |
| source: |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=alpindale/WizardLM-2-8x22B |
| name: Open LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: BBH (3-Shot) |
| type: BBH |
| args: |
| num_few_shot: 3 |
| metrics: |
| - type: acc_norm |
| value: 48.58 |
| name: normalized accuracy |
| source: |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=alpindale/WizardLM-2-8x22B |
| name: Open LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: MATH Lvl 5 (4-Shot) |
| type: hendrycks/competition_math |
| args: |
| num_few_shot: 4 |
| metrics: |
| - type: exact_match |
| value: 22.28 |
| name: exact match |
| source: |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=alpindale/WizardLM-2-8x22B |
| name: Open LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: GPQA (0-shot) |
| type: Idavidrein/gpqa |
| args: |
| num_few_shot: 0 |
| metrics: |
| - type: acc_norm |
| value: 17.56 |
| name: acc_norm |
| source: |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=alpindale/WizardLM-2-8x22B |
| name: Open LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: MuSR (0-shot) |
| type: TAUR-Lab/MuSR |
| args: |
| num_few_shot: 0 |
| metrics: |
| - type: acc_norm |
| value: 14.54 |
| name: acc_norm |
| source: |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=alpindale/WizardLM-2-8x22B |
| name: Open LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: MMLU-PRO (5-shot) |
| type: TIGER-Lab/MMLU-Pro |
| config: main |
| split: test |
| args: |
| num_few_shot: 5 |
| metrics: |
| - type: acc |
| value: 39.96 |
| name: accuracy |
| source: |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=alpindale/WizardLM-2-8x22B |
| name: Open LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: ENEM Challenge (No Images) |
| type: eduagarcia/enem_challenge |
| split: train |
| args: |
| num_few_shot: 3 |
| metrics: |
| - type: acc |
| value: 75.86 |
| name: accuracy |
| source: |
| url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=alpindale/WizardLM-2-8x22B |
| name: Open Portuguese LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: BLUEX (No Images) |
| type: eduagarcia-temp/BLUEX_without_images |
| split: train |
| args: |
| num_few_shot: 3 |
| metrics: |
| - type: acc |
| value: 65.79 |
| name: accuracy |
| source: |
| url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=alpindale/WizardLM-2-8x22B |
| name: Open Portuguese LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: OAB Exams |
| type: eduagarcia/oab_exams |
| split: train |
| args: |
| num_few_shot: 3 |
| metrics: |
| - type: acc |
| value: 56.45 |
| name: accuracy |
| source: |
| url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=alpindale/WizardLM-2-8x22B |
| name: Open Portuguese LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: Assin2 RTE |
| type: assin2 |
| split: test |
| args: |
| num_few_shot: 15 |
| metrics: |
| - type: f1_macro |
| value: 94.12 |
| name: f1-macro |
| source: |
| url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=alpindale/WizardLM-2-8x22B |
| name: Open Portuguese LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: Assin2 STS |
| type: eduagarcia/portuguese_benchmark |
| split: test |
| args: |
| num_few_shot: 15 |
| metrics: |
| - type: pearson |
| value: 79.32 |
| name: pearson |
| source: |
| url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=alpindale/WizardLM-2-8x22B |
| name: Open Portuguese LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: FaQuAD NLI |
| type: ruanchaves/faquad-nli |
| split: test |
| args: |
| num_few_shot: 15 |
| metrics: |
| - type: f1_macro |
| value: 76.97 |
| name: f1-macro |
| source: |
| url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=alpindale/WizardLM-2-8x22B |
| name: Open Portuguese LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: HateBR Binary |
| type: ruanchaves/hatebr |
| split: test |
| args: |
| num_few_shot: 25 |
| metrics: |
| - type: f1_macro |
| value: 82.06 |
| name: f1-macro |
| source: |
| url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=alpindale/WizardLM-2-8x22B |
| name: Open Portuguese LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: PT Hate Speech Binary |
| type: hate_speech_portuguese |
| split: test |
| args: |
| num_few_shot: 25 |
| metrics: |
| - type: f1_macro |
| value: 72.88 |
| name: f1-macro |
| source: |
| url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=alpindale/WizardLM-2-8x22B |
| name: Open Portuguese LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: tweetSentBR |
| type: eduagarcia/tweetsentbr_fewshot |
| split: test |
| args: |
| num_few_shot: 25 |
| metrics: |
| - type: f1_macro |
| value: 72.59 |
| name: f1-macro |
| source: |
| url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=alpindale/WizardLM-2-8x22B |
| name: Open Portuguese LLM Leaderboard |
| --- |
| |
|
|
|
|
| <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. |
|
|
|
|
|
|
|
|
|
|
| # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) |
| Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_alpindale__WizardLM-2-8x22B) |
|
|
| | Metric |Value| |
| |-------------------|----:| |
| |Avg. |32.61| |
| |IFEval (0-Shot) |52.72| |
| |BBH (3-Shot) |48.58| |
| |MATH Lvl 5 (4-Shot)|22.28| |
| |GPQA (0-shot) |17.56| |
| |MuSR (0-shot) |14.54| |
| |MMLU-PRO (5-shot) |39.96| |
|
|
|
|
| # Open Portuguese LLM Leaderboard Evaluation Results |
|
|
| Detailed results can be found [here](https://huggingface.co/datasets/eduagarcia-temp/llm_pt_leaderboard_raw_results/tree/main/alpindale/WizardLM-2-8x22B) and on the [🚀 Open Portuguese LLM Leaderboard](https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard) |
|
|
| | Metric | Value | |
| |--------------------------|---------| |
| |Average |**75.11**| |
| |ENEM Challenge (No Images)| 75.86| |
| |BLUEX (No Images) | 65.79| |
| |OAB Exams | 56.45| |
| |Assin2 RTE | 94.12| |
| |Assin2 STS | 79.32| |
| |FaQuAD NLI | 76.97| |
| |HateBR Binary | 82.06| |
| |PT Hate Speech Binary | 72.88| |
| |tweetSentBR | 72.59| |
|
|
|
|
