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Model: Aratako/Swallow-MoE-2x13B-v0.1 Source: Original Platform
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README.md
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README.md
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---
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base_model:
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- tokyotech-llm/Swallow-13b-instruct-hf
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- nitky/Superswallow-13b-v0.2
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license: llama2
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language:
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- ja
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tags:
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- mergekit
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- merge
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- MoE
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---
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# Swallow-MoE-2x13B-v0.1
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[**English description here**](#description)
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## 概要
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Llama-2ベースの学習済み日本語モデルである[tokyotech-llm/Swallow-13b-instruct-hf](https://huggingface.co/tokyotech-llm/Swallow-13b-instruct-hf)と、それを利用したマージモデルである[nitky/Superswallow-13b-v0.2](https://huggingface.co/nitky/Superswallow-13b-v0.2)
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を、[mergekit](https://github.com/cg123/mergekit)を使ってMoEを行い作成したモデルです。
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[GGUF版はこちら](https://huggingface.co/Aratako/Swallow-MoE-2x13B-v0.1-GGUF)
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以下2モデルを利用しています。
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- [tokyotech-llm/Swallow-13b-instruct-hf](https://huggingface.co/tokyotech-llm/Swallow-13b-instruct-hf)
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- [nitky/Superswallow-13b-v0.2](https://huggingface.co/nitky/Superswallow-13b-v0.2)
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## ライセンス
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Llama2ライセンスを継承しますが、それ以外にもこのマージモデルはLlama2ライセンス以外のライセンスの影響を受けます。
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- [nitky/Superswallow-13b-v0.2](https://huggingface.co/nitky/Superswallow-13b-v0.2)の利用により、[AI2 ImpACT license](https://allenai.org/impact-license)を継承している可能性があります。詳細は元モデルの概要をご確認ください。
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## ベンチマーク
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ベースとしたSwallow-13b-instruct-hf、Superswallow-13b-v0.2と本モデルの[japanese-mt-bench](https://github.com/Stability-AI/FastChat/tree/jp-stable/fastchat/llm_judge)の結果は以下の通りです。
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(シングルターン)
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|Model|Size|Coding|Extraction|Humanities|Math|Reasoning|Roleplay|STEM|Writing|avg_score|
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|---|---|---|---|---|---|---|---|---|---|---|
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| Swallow-13b-instruct-hf | 13B | 2.1 | 5.0 | 6.1 | 1.9 | 4.5 | 5.0 | 4.9 | 5.6 | 4.3875 |
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| Superswallow-13b-v0.2 | 13B | **2.7** | **6.3** | **8.4** | 2.2 | **5.9** | 6.8 | 7.2 | 6.8 | 5.7875 |
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| This model | 2x13B | 2.6 | 6.2 | **8.4** | **2.3** | 5.3 | **7.4** | **7.7** | **8.4** | **6.0375** |
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**ベンチマークに使用したプロンプト**
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- Swallow-13b-instruct-hf, Superswallow-13b-v0.2
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```
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以下に、あるタスクを説明する指示があり、それに付随する入力が更なる文脈を提供しています。リクエストを適切に完了するための回答を記述してください。
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### 指示:
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{instruction}
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### 応答:
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```
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- Swallow-MoE-2x13B-v0.1
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```
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### 指示:
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{instruction}
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### 応答:
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```
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## Description
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This model is created using MoE (Mixture of Experts) through mergekit based on [tokyotech-llm/Swallow-13b-instruct-hf](https://huggingface.co/tokyotech-llm/Swallow-13b-instruct-hf) and [nitky/Superswallow-13b-v0.2](https://huggingface.co/nitky/Superswallow-13b-v0.2).
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[Click here for the GGUF version](https://huggingface.co/Aratako/Swallow-MoE-2x13B-v0.1-GGUF)
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It utilizes the following two models:
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- [tokyotech-llm/Swallow-13b-instruct-hf](https://huggingface.co/tokyotech-llm/Swallow-13b-instruct-hf)
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- [nitky/Superswallow-13b-v0.2](https://huggingface.co/nitky/Superswallow-13b-v0.2)
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## License
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While inheriting the Llama2 license, this merged model is also subject to other licenses due to its use of models beyond Llama2.
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- Due to the use of [nitky/Superswallow-13b-v0.2](https://huggingface.co/nitky/Superswallow-13b-v0.2), it may inherit the [AI2 ImpACT license](https://allenai.org/impact-license). Please refer to the original model's overview for details.
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## Benchmark
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The results of this model and the base Swallow-13b-instruct-hf, Superswallow-13b-v0.2 on japanese-mt-bench are as follows.
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(Single turn)
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|Model|Size|Coding|Extraction|Humanities|Math|Reasoning|Roleplay|STEM|Writing|avg_score|
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|---|---|---|---|---|---|---|---|---|---|---|
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| Swallow-13b-instruct-hf | 13B | 2.1 | 5.0 | 6.1 | 1.9 | 4.5 | 5.0 | 4.9 | 5.6 | 4.3875 |
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| Superswallow-13b-v0.2 | 13B | **2.7** | **6.3** | **8.4** | 2.2 | **5.9** | 6.8 | 7.2 | 6.8 | 5.7875 |
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| This model | 2x13B | 2.6 | 6.2 | **8.4** | **2.3** | 5.3 | **7.4** | **7.7** | **8.4** | **6.0375** |
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**Prompt used for benchmark**
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- Swallow-13b-instruct-hf, Superswallow-13b-v0.2
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```
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以下に、あるタスクを説明する指示があり、それに付随する入力が更なる文脈を提供しています。リクエストを適切に完了するための回答を記述してください。
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### 指示:
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{instruction}
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### 応答:
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```
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- Swallow-MoE-2x13B-v0.1
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```
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### 指示:
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{instruction}
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### 応答:
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```
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## Merge config
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[mergekit_config.yml](./mergekit_moe_config.yml)
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```yaml
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base_model: ./Superswallow-13b-v0.2
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gate_mode: random
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dtype: bfloat16
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experts:
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- source_model: ./Superswallow-13b-v0.2
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positive_prompts: []
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- source_model: ./Swallow-13b-instruct-hf
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positive_prompts: []
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tokenizer_source: union
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```
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