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README.md
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Quantization made by Richard Erkhov.
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[Github](https://github.com/RichardErkhov)
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[Discord](https://discord.gg/pvy7H8DZMG)
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[Request more models](https://github.com/RichardErkhov/quant_request)
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youri-7b - GGUF
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- Model creator: https://huggingface.co/rinna/
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- Original model: https://huggingface.co/rinna/youri-7b/
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| Name | Quant method | Size |
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| ---- | ---- | ---- |
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| [youri-7b.Q2_K.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.Q2_K.gguf) | Q2_K | 2.36GB |
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| [youri-7b.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.IQ3_XS.gguf) | IQ3_XS | 2.6GB |
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| [youri-7b.IQ3_S.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.IQ3_S.gguf) | IQ3_S | 2.75GB |
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| [youri-7b.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.Q3_K_S.gguf) | Q3_K_S | 2.75GB |
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| [youri-7b.IQ3_M.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.IQ3_M.gguf) | IQ3_M | 2.9GB |
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| [youri-7b.Q3_K.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.Q3_K.gguf) | Q3_K | 3.07GB |
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| [youri-7b.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.Q3_K_M.gguf) | Q3_K_M | 3.07GB |
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| [youri-7b.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.Q3_K_L.gguf) | Q3_K_L | 3.35GB |
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| [youri-7b.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.IQ4_XS.gguf) | IQ4_XS | 3.4GB |
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| [youri-7b.Q4_0.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.Q4_0.gguf) | Q4_0 | 3.56GB |
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| [youri-7b.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.IQ4_NL.gguf) | IQ4_NL | 3.58GB |
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| [youri-7b.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.Q4_K_S.gguf) | Q4_K_S | 3.59GB |
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| [youri-7b.Q4_K.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.Q4_K.gguf) | Q4_K | 3.8GB |
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| [youri-7b.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.Q4_K_M.gguf) | Q4_K_M | 3.8GB |
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| [youri-7b.Q4_1.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.Q4_1.gguf) | Q4_1 | 3.95GB |
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| [youri-7b.Q5_0.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.Q5_0.gguf) | Q5_0 | 4.33GB |
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| [youri-7b.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.Q5_K_S.gguf) | Q5_K_S | 4.33GB |
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| [youri-7b.Q5_K.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.Q5_K.gguf) | Q5_K | 4.45GB |
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| [youri-7b.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.Q5_K_M.gguf) | Q5_K_M | 4.45GB |
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| [youri-7b.Q5_1.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.Q5_1.gguf) | Q5_1 | 4.72GB |
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| [youri-7b.Q6_K.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.Q6_K.gguf) | Q6_K | 5.15GB |
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| [youri-7b.Q8_0.gguf](https://huggingface.co/RichardErkhov/rinna_-_youri-7b-gguf/blob/main/youri-7b.Q8_0.gguf) | Q8_0 | 6.67GB |
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Original model description:
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---
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language:
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- ja
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- en
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license: llama2
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datasets:
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- mc4
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- wikipedia
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- EleutherAI/pile
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- oscar-corpus/colossal-oscar-1.0
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- cc100
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thumbnail: https://github.com/rinnakk/japanese-pretrained-models/blob/master/rinna.png
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inference: false
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model-index:
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- name: youri-7b
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 49.06
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rinna/youri-7b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 74.89
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rinna/youri-7b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 42.22
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rinna/youri-7b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 36.03
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rinna/youri-7b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 71.82
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rinna/youri-7b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 8.64
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rinna/youri-7b
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name: Open LLM Leaderboard
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---
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# `rinna/youri-7b`
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![rinna-icon](./rinna.png)
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# Overview
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We conduct continual pre-training of [llama2-7b](https://huggingface.co/meta-llama/Llama-2-7b-hf) on **40B** tokens from a mixture of Japanese and English datasets. The continual pre-training significantly improves the model's performance on Japanese tasks.
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The name `youri` comes from the Japanese word [`妖狸/ようり/Youri`](https://ja.wikipedia.org/wiki/%E5%8C%96%E3%81%91%E7%8B%B8), which is a kind of Japanese mythical creature ([`妖怪/ようかい/Youkai`](https://ja.wikipedia.org/wiki/%E5%A6%96%E6%80%AA)).
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* **Library**
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The model was trained using code based on [EleutherAI/gpt-neox](https://github.com/EleutherAI/gpt-neox).
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* **Model architecture**
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A 32-layer, 4096-hidden-size transformer-based language model. Refer to the [llama2 paper](https://arxiv.org/abs/2307.09288) for architecture details.
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* **Continual pre-training**
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The model was initialized with the [llama2-7b](https://huggingface.co/meta-llama/Llama-2-7b-hf) model and continually trained on around **40B** tokens from a mixture of the following corpora
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- [Japanese CC-100](http://data.statmt.org/cc-100/ja.txt.xz)
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- [Japanese C4](https://huggingface.co/datasets/mc4)
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- [Japanese OSCAR](https://huggingface.co/datasets/oscar-corpus/colossal-oscar-1.0)
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- [The Pile](https://huggingface.co/datasets/EleutherAI/pile)
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- [Wikipedia](https://dumps.wikimedia.org/other/cirrussearch)
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- rinna curated Japanese dataset
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* **Contributors**
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- [Tianyu Zhao](https://huggingface.co/tianyuz)
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- [Akio Kaga](https://huggingface.co/rakaga)
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- [Kei Sawada](https://huggingface.co/keisawada)
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---
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# Benchmarking
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Please refer to [rinna's LM benchmark page](https://rinnakk.github.io/research/benchmarks/lm/index.html).
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---
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# How to use the model
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~~~~python
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("rinna/youri-7b")
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model = AutoModelForCausalLM.from_pretrained("rinna/youri-7b")
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if torch.cuda.is_available():
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model = model.to("cuda")
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text = "西田幾多郎は、"
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token_ids = tokenizer.encode(text, add_special_tokens=False, return_tensors="pt")
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with torch.no_grad():
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output_ids = model.generate(
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token_ids.to(model.device),
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max_new_tokens=200,
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min_new_tokens=200,
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do_sample=True,
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temperature=1.0,
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top_p=0.95,
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pad_token_id=tokenizer.pad_token_id,
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bos_token_id=tokenizer.bos_token_id,
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eos_token_id=tokenizer.eos_token_id
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)
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output = tokenizer.decode(output_ids.tolist()[0])
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print(output)
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"""
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西田幾多郎は、プラトンの復権を主張し、対する従来の西洋哲学は、近代の合理主義哲学に委ね、「従来の哲学は破 壊されてしまった」と述べている。 西田幾多郎は、西洋近代哲学の「徹底的な検討」を拒んだ。それは、「現代的理解の脆弱性を補う筈の、従来のヨーロッパに伝わる哲学的な方法では到底それができなかったからである」とい
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"""
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~~~~
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---
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# Tokenization
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The model uses the original llama-2 tokenizer.
|
242 |
+
|
243 |
+
---
|
244 |
+
|
245 |
+
# How to cite
|
246 |
+
```bibtex
|
247 |
+
@misc{rinna-youri-7b,
|
248 |
+
title = {rinna/youri-7b},
|
249 |
+
author = {Zhao, Tianyu and Kaga, Akio and Sawada, Kei},
|
250 |
+
url = {https://huggingface.co/rinna/youri-7b}
|
251 |
+
}
|
252 |
+
|
253 |
+
@inproceedings{sawada2024release,
|
254 |
+
title = {Release of Pre-Trained Models for the {J}apanese Language},
|
255 |
+
author = {Sawada, Kei and Zhao, Tianyu and Shing, Makoto and Mitsui, Kentaro and Kaga, Akio and Hono, Yukiya and Wakatsuki, Toshiaki and Mitsuda, Koh},
|
256 |
+
booktitle = {Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)},
|
257 |
+
month = {5},
|
258 |
+
year = {2024},
|
259 |
+
pages = {13898--13905},
|
260 |
+
url = {https://aclanthology.org/2024.lrec-main.1213},
|
261 |
+
note = {\url{https://arxiv.org/abs/2404.01657}}
|
262 |
+
}
|
263 |
+
```
|
264 |
+
---
|
265 |
+
|
266 |
+
# References
|
267 |
+
```bibtex
|
268 |
+
@software{gpt-neox-library,
|
269 |
+
title = {{GPT}-{N}eo{X}: Large Scale Autoregressive Language Modeling in {P}y{T}orch},
|
270 |
+
author = {Andonian, Alex and Anthony, Quentin and Biderman, Stella and Black, Sid and Gali, Preetham and Gao, Leo and Hallahan, Eric and Levy-Kramer, Josh and Leahy, Connor and Nestler, Lucas and Parker, Kip and Pieler, Michael and Purohit, Shivanshu and Songz, Tri and Phil, Wang and Weinbach, Samuel},
|
271 |
+
doi = {10.5281/zenodo.5879544},
|
272 |
+
month = {8},
|
273 |
+
year = {2021},
|
274 |
+
version = {0.0.1},
|
275 |
+
url = {https://www.github.com/eleutherai/gpt-neox}
|
276 |
+
}
|
277 |
+
```
|
278 |
+
---
|
279 |
+
|
280 |
+
# License
|
281 |
+
[The llama2 license](https://ai.meta.com/llama/license/)
|
282 |
+
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
|
283 |
+
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_rinna__youri-7b)
|
284 |
+
|
285 |
+
| Metric |Value|
|
286 |
+
|---------------------------------|----:|
|
287 |
+
|Avg. |47.11|
|
288 |
+
|AI2 Reasoning Challenge (25-Shot)|49.06|
|
289 |
+
|HellaSwag (10-Shot) |74.89|
|
290 |
+
|MMLU (5-Shot) |42.22|
|
291 |
+
|TruthfulQA (0-shot) |36.03|
|
292 |
+
|Winogrande (5-shot) |71.82|
|
293 |
+
|GSM8k (5-shot) | 8.64|
|
294 |
+
|
295 |
+
|
296 |
+
|