50 lines
2.0 KiB
Markdown
50 lines
2.0 KiB
Markdown
<!--Copyright 2024 JetMoe team and The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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# JetMoe
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## Overview
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**JetMoe-8B** is an 8B Mixture-of-Experts (MoE) language model developed by [Yikang Shen](https://scholar.google.com.hk/citations?user=qff5rRYAAAAJ) and [MyShell](https://myshell.ai/).
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JetMoe project aims to provide a LLaMA2-level performance and efficient language model with a limited budget.
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To achieve this goal, JetMoe uses a sparsely activated architecture inspired by the [ModuleFormer](https://arxiv.org/abs/2306.04640).
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Each JetMoe block consists of two MoE layers: Mixture of Attention Heads and Mixture of MLP Experts.
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Given the input tokens, it activates a subset of its experts to process them.
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This sparse activation schema enables JetMoe to achieve much better training throughput than similar size dense models.
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The training throughput of JetMoe-8B is around 100B tokens per day on a cluster of 96 H100 GPUs with a straightforward 3-way pipeline parallelism strategy.
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This model was contributed by [Yikang Shen](https://huggingface.co/YikangS).
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## JetMoeConfig
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[[autodoc]] JetMoeConfig
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## JetMoeModel
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[[autodoc]] JetMoeModel
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- forward
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## JetMoeForCausalLM
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[[autodoc]] JetMoeForCausalLM
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- forward
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## JetMoeForSequenceClassification
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[[autodoc]] JetMoeForSequenceClassification
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- forward
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