Model Overview
Description
Qwen2 is the new series of Qwen large language models for language understanding, language generation, multilingual capability, coding, mathematics, and reasoning. For Qwen2, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters, including a Mixture-of-Experts model. This repo contains the 7B Qwen2 base language model.
Compared with the state-of-the-art open source language models, including the previously released Qwen1.5, Qwen2 has generally surpassed most open source models and demonstrated competitiveness against proprietary models across a series of benchmarks targeting for language understanding, language generation, multilingual capability, coding, mathematics, and reasoning tasks, etc.
This model is ready for commercial use.
Third-Party Community Consideration
This model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case; see link to Qwen's (Model Card).
License, Acceptable Use, and Research Privacy Policy
By using this model, you are agreeing to the terms and conditions of the Apache 2.0
Model Developer: Qwen
Model Update Date: August 8, 2024
Model Architecture
Architecture Type: Transformer
Network Architecture: Qwen
Input
Input Type: Text
Input Format: String
Input Parameters: max_tokens, temperature, top_p, stop, frequency_penalty, presence_penalty, seed
Output
Output Type: Text
Output Format: String
Software Integration
[Preferred/Supported] Operating System(s): Linux
Model Version(s):
The instruction-tuned 7B Qwen2 model, Qwen2-7B-Instruct
Training Dataset:
Link: [Unknown]
Data Collection Method by dataset
- [Unknown]
Labeling Method by dataset
- [Unknown]
Properties (Quantity, Dataset Descriptions, Sensor(s)): Unknown
Evaluation Dataset:
Link: See Performance section of the Hugging Face Qwen2-7B Model Card
Inference
Engine: TensorRT-LLM
Test Hardware: L40
Ethical Considerations:
NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.
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