English
What is Mistral-Nemo-Instruct-2407?
Mistral-Nemo-Instruct-2407 is a large language model (LLM) developed by Mistral AI and NVIDIA. This model is a guided fine-tuning version of Mistral-Nemo-Base-2407. It is trained on multilingual and code data, significantly outperforming similar or smaller models.
Key Features:
Supports training on multilingual and code data
Has a 128k context window
Can replace Mistral 7B
Model Architecture:
40 layers
5120 dimensions
128 attention heads
1436 hidden dimensions
32 attention heads per layer
8 key-value attention heads (GQA)
2^17 vocabulary size (approximately 128k)
Rotational embeddings (theta=1M)
Performance:
Outperforms other models in benchmarks like HellaSwag, Winogrande, and OpenBookQA
Target Audience:
Developers and researchers who need to handle large volumes of text and multilingual data
Usage Scenarios:
Text generation based on specific instructions
Machine translation in multilingual environments
Retrieving current weather information through function calls
Product Highlights:
Trained on multilingual and code data
128k context window
Powerful text processing capabilities with its architecture
Outstanding performance in various benchmarks
Getting Started Guide:
1. Install mistral_inference to ensure compatibility with the model
2. Download model files including params.json, consolidated.safetensors, and tekken.json
3. Use mistral-chat CLI to interact with the model
4. Generate text using the transformers framework and pipeline functions
5. Retrieve current weather information using Tool and Function classes
6. Adjust model parameters such as temperature to optimize outputs
7. Refer to the model card for detailed information and usage limitations
