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converted via this PR |
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https://github.com/ggerganov/llama.cpp/pull/8604 |
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original model https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407 |
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license: apache-2.0 |
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language: |
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- en |
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- fr |
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- de |
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- es |
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- it |
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- pt |
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- ru |
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- zh |
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- ja |
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--- |
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# Model Card for Mistral-Nemo-Instruct-2407 |
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The Mistral-Nemo-Instruct-2407 Large Language Model (LLM) is an instruct fine-tuned version of the [Mistral-Nemo-Base-2407](https://huggingface.co/mistralai/Mistral-Nemo-Base-2407). Trained jointly by Mistral AI and NVIDIA, it significantly outperforms existing models smaller or similar in size. |
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For more details about this model please refer to our release [blog post](https://mistral.ai/news/mistral-nemo/). |
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## Key features |
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- Released under the **Apache 2 License** |
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- Pre-trained and instructed versions |
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- Trained with a **128k context window** |
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- Trained on a large proportion of **multilingual and code data** |
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- Drop-in replacement of Mistral 7B |
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## Model Architecture |
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Mistral Nemo is a transformer model, with the following architecture choices: |
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- **Layers:** 40 |
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- **Dim:** 5,120 |
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- **Head dim:** 128 |
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- **Hidden dim:** 14,436 |
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- **Activation Function:** SwiGLU |
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- **Number of heads:** 32 |
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- **Number of kv-heads:** 8 (GQA) |
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- **Vocabulary size:** 2**17 ~= 128k |
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- **Rotary embeddings (theta = 1M)** |
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## Metrics |
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### Main Benchmarks |
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| Benchmark | Score | |
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| --- | --- | |
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| HellaSwag (0-shot) | 83.5% | |
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| Winogrande (0-shot) | 76.8% | |
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| OpenBookQA (0-shot) | 60.6% | |
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| CommonSenseQA (0-shot) | 70.4% | |
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| TruthfulQA (0-shot) | 50.3% | |
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| MMLU (5-shot) | 68.0% | |
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| TriviaQA (5-shot) | 73.8% | |
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| NaturalQuestions (5-shot) | 31.2% | |
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### Multilingual Benchmarks (MMLU) |
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| Language | Score | |
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| --- | --- | |
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| French | 62.3% | |
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| German | 62.7% | |
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| Spanish | 64.6% | |
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| Italian | 61.3% | |
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| Portuguese | 63.3% | |
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| Russian | 59.2% | |
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| Chinese | 59.0% | |
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| Japanese | 59.0% | |