Mistral Nemo Instruct 2407 EU AI Act Compliance Profile

Model Card for Mistral-Nemo-Instruct-2407

The Mistral-Nemo-Instruct-2407 Large Language Model (LLM) is an instruct fine-tuned version of the Mistral-Nemo-Base-2407. Trained jointly by Mistral AI and NVIDIA, it significantly outperforms existing models smaller or similar in size.

For more details about this model please refer to our release blog post.

Key features

• Released under the Apache 2 License
• Pre-trained and instructed versions
• Trained with a 128k context window
• Trained on a large proportion of multilingual and code data
• Drop-in replacement of Mistral 7B

Model Architecture

Mistral Nemo is a transformer model, with the following architecture choices:

• Layers: 40
• Dim: 5,120
• Head dim: 128
• Hidden dim: 14,336
• Activation Function: SwiGLU
• Number of heads: 32
• Number of kv-heads: 8 (GQA)
• Vocabulary size: 2**17 ~= 128k
• Rotary embeddings (theta = 1M)

Metrics

Main Benchmarks

| Benchmark | Score | | --- | --- | | HellaSwag (0-shot) | 83.5% | | Winogrande (0-shot) | 76.8% | | OpenBookQA (0-shot) | 60.6% | | CommonSenseQA (0-shot) | 70.4% | | TruthfulQA (0-shot) | 50.3% | | MMLU (5-shot) | 68.0% | | TriviaQA (5-shot) | 73.8% | | NaturalQuestions (5-shot) | 31.2% |

Multilingual Benchmarks (MMLU)

| Language | Score | | --- | --- | | French | 62.3% | | German | 62.7% | | Spanish | 64.6% | | Italian | 61.3% | | Portuguese | 63.3% | | Russian | 59.2% | | Chinese | 59.0% | | Japanese | 59.0% |

Usage

The model can be used with three different frameworks

• mistral_inference: See here
• transformers: See here
• NeMo: See [nvidia/Mistral-NeMo-12B-In

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Base Model