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README.md
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[TransNormerLLM](https://arxiv.org/abs/2307.14995) evolving from [TransNormer](https://arxiv.org/abs/2210.10340), standing out as the first LLM within the linear transformer architecture. Additionally, it distinguishes itself by being the first non-Transformer LLM to exceed both traditional Transformer and other efficient Transformer models (such as, RetNet and Mamba) in terms of speed and performance.
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# TransNormerLLM3
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- **TransNormerLLM3-15B** features **14.83 billion** parameters. It is structured with **42 layers**, includes **40 attention heads**, and has a total **embedding size of 5120**.
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- **TransNormerLLM3-15B** is purely intergrated with **[Lightning Attention-2](http://arxiv.org/abs/2401.04658)**, which can maintain a **stable TGS** during training of **unlimited sequence lengths**, up until encountering firm limitations like GPU memory constraints.
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- **Titoken** tokenizer is used with a total **vocabulary size** of about **100,000**.
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<p align="center">
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<img src="./images/TransNormer3.jpg" width="65%" />
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</p>
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# Released Weights
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| param | token | Hugging Face
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| **15B** | 50B |
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| **15B** | 100B | 🤗[step26000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step26000-100Btokens)
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| **15B** | 150B | 🤗[step39000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step39000-150Btokens)
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| **15B** | 200B | 🤗[step52000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step52000-200Btokens)
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| **15B** | 250B | 🤗[step65000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step65000-250Btokens)
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| **15B** | 300B | 🤗[step78000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step78000-300Btokens)
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| **15B** | 350B | 🤗[step92000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step92000-350Btokens)
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| **15B** | 400B | 🤗[step105000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step105000-400Btokens)
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| **15B** | 450B | 🤗[step118000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step118000-450Btokens)
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| **15B** | 500B | 🤗[step131000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step131000-500Btokens)
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| **15B** | 550B | 🤗[step144000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step144000-550Btokens)
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| **15B** | 600B | 🤗[step157000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step157000-600Btokens)
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| **15B** | 650B | 🤗[step170000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step170000-650Btokens)
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| **15B** | 700B | 🤗[step183000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step183000-700Btokens)
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| **15B** | 750B | 🤗[step195500](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step195500-750Btokens)
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| **15B** | 800B | 🤗[step209000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step209000-800Btokens)
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| **15B** | 850B | 🤗[step222000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step222000-850Btokens)
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| **15B** | 900B | 🤗[step235000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step235000-900Btokens)
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# Benchmark Results
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The evaluations of all models are conducted using the official settings and the [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness) framework.
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| Model | P | T
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| ----------------------- | --- |
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| **TransNormerLLM3-15B** | 15 | 0.05
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| **TransNormerLLM3-15B** | 15 | 0.10
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| **TransNormerLLM3-15B** | 15 | 0.15
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| **TransNormerLLM3-15B** | 15 | 0.20
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| **TransNormerLLM3-15B** | 15 | 0.25
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| **TransNormerLLM3-15B** | 15 | 0.35
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| **TransNormerLLM3-15B** | 15 | 0.50
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| **TransNormerLLM3-15B** | 15 | 0.55
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| **TransNormerLLM3-15B** | 15 | 0.90
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> **P**: parameter size (billion). **T**: tokens (trillion). **BoolQ**: acc. **PIQA**: acc. **HellaSwag**: acc_norm. **WinoGrande**: acc. **ARC-easy**: acc. **ARC-challenge**: acc_norm. **OpenBookQA**: acc_norm. **MMLU**: 5-shot acc. **C-Eval**: 5-shot acc.
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@@ -136,6 +157,14 @@ If you wish to cite our work, please use the following reference:
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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<p align="center">
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[TransNormerLLM](https://arxiv.org/abs/2307.14995) evolving from [TransNormer](https://arxiv.org/abs/2210.10340), standing out as the first LLM within the linear transformer architecture. Additionally, it distinguishes itself by being the first non-Transformer LLM to exceed both traditional Transformer and other efficient Transformer models (such as, RetNet and Mamba) in terms of speed and performance.
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> Update@Apr.7: We plan to increase the sequence length in pre-training stage to **10 million**: https://twitter.com/opennlplab/status/1776894730015789300
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# TransNormerLLM3
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- **TransNormerLLM3-15B** features **14.83 billion** parameters. It is structured with **42 layers**, includes **40 attention heads**, and has a total **embedding size of 5120**.
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- **TransNormerLLM3-15B** is purely intergrated with **[Lightning Attention-2](http://arxiv.org/abs/2401.04658)**, which can maintain a **stable TGS** during training of **unlimited sequence lengths**, up until encountering firm limitations like GPU memory constraints.
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- **Titoken** tokenizer is used with a total **vocabulary size** of about **100,000**.
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- Our **training framework** has been enhanced with integration to **[LASP](https://arxiv.org/abs/2404.02882) (Linear Attention Sequence Parallelism)**, allowing for sequence parallelism within linear attention models.
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- Our **training framework** now supprts **[CO2](https://arxiv.org/abs/2401.16265)**, which introduces **local updates** and **asynchronous communication** into distributed data parallel training, achieving **full overlap** of communication and computation.
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<p align="center">
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<img src="./images/TransNormer3.jpg" width="65%" />
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</p>
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# Released Weights
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| param | token | Hugging Face | Model Scope | Wisemodel |
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| :-----: | :---: | :-----------------------------------------------------------------------------------------------------------------------: | :---------: | :-------: |
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| **15B** | 50B | 🤗[step13000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step13000-50Btokens) | 🤖 | 🐯 |
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| **15B** | 100B | 🤗[step26000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step26000-100Btokens) | 🤖 | 🐯 |
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| **15B** | 150B | 🤗[step39000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step39000-150Btokens) | 🤖 | 🐯 |
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| **15B** | 200B | 🤗[step52000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step52000-200Btokens) | 🤖 | 🐯 |
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| **15B** | 250B | 🤗[step65000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step65000-250Btokens) | 🤖 | 🐯 |
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| **15B** | 300B | 🤗[step78000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step78000-300Btokens) | 🤖 | 🐯 |
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| **15B** | 350B | 🤗[step92000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step92000-350Btokens) | 🤖 | 🐯 |
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| **15B** | 400B | 🤗[step105000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step105000-400Btokens) | 🤖 | 🐯 |
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| **15B** | 450B | 🤗[step118000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step118000-450Btokens) | 🤖 | 🐯 |
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| **15B** | 500B | 🤗[step131000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step131000-500Btokens) | 🤖 | 🐯 |
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| **15B** | 550B | 🤗[step144000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step144000-550Btokens) | 🤖 | 🐯 |
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| **15B** | 600B | 🤗[step157000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step157000-600Btokens) | 🤖 | 🐯 |
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| **15B** | 650B | 🤗[step170000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step170000-650Btokens) | 🤖 | 🐯 |
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| **15B** | 700B | 🤗[step183000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step183000-700Btokens) | 🤖 | 🐯 |
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| **15B** | 750B | 🤗[step195500](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step195500-750Btokens) | 🤖 | 🐯 |
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| **15B** | 800B | 🤗[step209000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step209000-800Btokens) | 🤖 | 🐯 |
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| **15B** | 850B | 🤗[step222000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step222000-850Btokens) | 🤖 | 🐯 |
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| **15B** | 900B | 🤗[step235000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step235000-900Btokens) | 🤖 | 🐯 |
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| **15B** | 950B | 🤗[step248000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step248000-950Btokens) | 🤖 | 🐯 |
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| **15B** | 1000B | 🤗[step261000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step261000-1000Btokens) | 🤖 | 🐯 |
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| **15B** | 1050B | 🤗[step274000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step274000-1050Btokens) | 🤖 | 🐯 |
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| **15B** | 1100B | 🤗[step287000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step287000-1100Btokens) | 🤖 | 🐯 |
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| **15B** | 1150B | 🤗[step300000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step300000-1150Btokens) | 🤖 | 🐯 |
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| **15B** | 1200B | 🤗[step313500](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step313500-1200Btokens) | 🤖 | 🐯 |
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| **15B** | 1250B | 🤗[step326000](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step287000-1250Btokens) | 🤖 | 🐯 |
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| **15B** | 1300B | 🤗[step339500](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/step326000-1300Btokens) | 🤖 | 🐯 |
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| **15B** | 1345B | 🤗[stage1](https://huggingface.co/OpenNLPLab/TransNormerLLM3-15B-Intermediate-Checkpoints/tree/stage1-1345Btokens) | 🤖 | 🐯 |
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# Benchmark Results
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The evaluations of all models are conducted using the official settings and the [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness) framework.
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| Model | P | T | BoolQ | PIQA | HS | WG | ARC-e | ARC-c | OBQA | C-Eval | MMLU |
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| ----------------------- | --- | ------ | ----- | ----- | ----- | ----- | ----- | ----- | ----- | ------ | ----- |
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| **TransNormerLLM3-15B** | 15 | 0.05 | 62.08 | 72.52 | 55.55 | 57.14 | 62.12 | 31.14 | 32.40 | 26.18 | 27.50 |
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| **TransNormerLLM3-15B** | 15 | 0.10 | 63.98 | 74.70 | 61.09 | 61.33 | 65.95 | 34.64 | 35.60 | 25.38 | 27.40 |
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| **TransNormerLLM3-15B** | 15 | 0.15 | 60.34 | 75.08 | 63.99 | 62.04 | 64.56 | 34.90 | 35.20 | 22.64 | 26.60 |
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| **TransNormerLLM3-15B** | 15 | 0.20 | 52.05 | 74.48 | 64.72 | 62.75 | 66.16 | 35.15 | 36.80 | 27.25 | 30.80 |
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| **TransNormerLLM3-15B** | 15 | 0.25 | 66.70 | 76.50 | 66.51 | 64.80 | 66.84 | 36.18 | 39.40 | 30.87 | 36.10 |
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| **TransNormerLLM3-15B** | 15 | 0.30 | 67.00 | 76.50 | 67.17 | 64.40 | 66.29 | 36.77 | 38.80 | 33.99 | 37.60 |
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| **TransNormerLLM3-15B** | 15 | 0.35 | 65.78 | 75.46 | 67.88 | 66.54 | 67.34 | 38.57 | 39.60 | 36.02 | 39.20 |
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| **TransNormerLLM3-15B** | 15 | 0.40 | 67.34 | 75.24 | 68.51 | 66.22 | 68.94 | 40.10 | 39.20 | 36.91 | 41.10 |
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| **TransNormerLLM3-15B** | 15 | 0.45 | 69.02 | 76.28 | 69.11 | 63.77 | 65.82 | 36.01 | 39.40 | 37.17 | 42.80 |
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| **TransNormerLLM3-15B** | 15 | 0.50 | 66.15 | 77.09 | 69.75 | 65.11 | 68.56 | 35.84 | 39.60 | 39.81 | 42.00 |
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| **TransNormerLLM3-15B** | 15 | 0.55 | 70.24 | 74.05 | 69.96 | 65.75 | 65.61 | 36.69 | 38.60 | 40.08 | 44.00 |
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| **TransNormerLLM3-15B** | 15 | 0.60 | 74.34 | 75.68 | 70.44 | 66.22 | 69.36 | 38.40 | 38.40 | 41.05 | 45.30 |
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| **TransNormerLLM3-15B** | 15 | 0.65 | 73.15 | 76.55 | 71.60 | 66.46 | 69.65 | 39.68 | 40.80 | 41.20 | 44.90 |
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| **TransNormerLLM3-15B** | 15 | 0.70 | 73.79 | 78.18 | 73.26 | 67.56 | 71.21 | 43.60 | 40.80 | 43.46 | 47.00 |
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| **TransNormerLLM3-15B** | 15 | 0.75 | 76.45 | 78.07 | 74.22 | 69.30 | 71.21 | 43.43 | 42.20 | 43.46 | 47.80 |
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| **TransNormerLLM3-15B** | 15 | 0.80 | 76.97 | 78.84 | 74.95 | 69.85 | 72.14 | 43.52 | 41.20 | 45.21 | 49.41 |
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| **TransNormerLLM3-15B** | 15 | 0.85 | 72.75 | 78.35 | 75.91 | 70.48 | 74.58 | 45.22 | 41.20 | 46.27 | 49.36 |
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| **TransNormerLLM3-15B** | 15 | 0.90 | 76.09 | 77.91 | 76.49 | 70.88 | 72.14 | 42.92 | 40.20 | 45.70 | 50.15 |
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| **TransNormerLLM3-15B** | 15 | 0.95 | 74.28 | 78.24 | 76.63 | 72.22 | 74.12 | 44.11 | 42.40 | 46.25 | 51.43 |
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| **TransNormerLLM3-15B** | 15 | 1.00 | 74.62 | 79.16 | 77.35 | 72.22 | 73.86 | 45.14 | 43.40 | 47.90 | 51.65 |
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| **TransNormerLLM3-15B** | 15 | 1.05 | 76.36 | 78.94 | 77.15 | 71.35 | 74.66 | 44.45 | 42.80 | 45.87 | 52.28 |
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| **TransNormerLLM3-15B** | 15 | 1.10 | 76.88 | 78.73 | 77.62 | 70.88 | 74.41 | 45.48 | 42.80 | 49.78 | 53.01 |
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| **TransNormerLLM3-15B** | 15 | 1.15 | 72.87 | 79.43 | 78.12 | 72.85 | 74.75 | 46.16 | 43.20 | 49.80 | 53.04 |
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| **TransNormerLLM3-15B** | 15 | 1.20 | 79.48 | 78.67 | 78.45 | 72.93 | 75.42 | 44.37 | 43.60 | 49.33 | 53.80 |
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| **TransNormerLLM3-15B** | 15 | 1.25 | 79.17 | 79.16 | 78.81 | 72.93 | 75.13 | 45.99 | 43.60 | 50.44 | 54.19 |
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| **TransNormerLLM3-15B** | 15 | 1.30 | 78.41 | 79.00 | 78.39 | 71.90 | 74.33 | 45.05 | 42.80 | 52.24 | 54.41 |
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| **TransNormerLLM3-15B** | 15 | stage1 | 78.75 | 79.27 | 78.33 | 71.35 | 75.97 | 46.42 | 45.00 | 50.25 | 54.50 |
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> **P**: parameter size (billion). **T**: tokens (trillion). **BoolQ**: acc. **PIQA**: acc. **HellaSwag**: acc_norm. **WinoGrande**: acc. **ARC-easy**: acc. **ARC-challenge**: acc_norm. **OpenBookQA**: acc_norm. **MMLU**: 5-shot acc. **C-Eval**: 5-shot acc.
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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@misc{sun2024linear,
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title={Linear Attention Sequence Parallelism},
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author={Weigao Sun and Zhen Qin and Dong Li and Xuyang Shen and Yu Qiao and Yiran Zhong},
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year={2024},
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eprint={2404.02882},
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archivePrefix={arXiv},
|
| 166 |
+
primaryClass={cs.LG}
|
| 167 |
+
}
|
| 168 |
```
|
| 169 |
|
| 170 |
<p align="center">
|