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Tencent-Hunyuan-Large

Industry-leading open source large-scale hybrid expert model

#Artificial Intelligence
#natural language processing
#Open source
#computer vision
#mixed expert model
#scientific tasks
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Tencent-Hunyuan-Large

Product Details

Tencent-Hunyuan-Large (Hunyuan Large Model) is an industry-leading open source large-scale hybrid expert (MoE) model launched by Tencent, with 389 billion total parameters and 52 billion activation parameters. The model has made significant progress in fields such as natural language processing, computer vision, and scientific tasks, especially in processing long-context input and improving long-context task processing capabilities. The open source of the Hunyuan large model aims to inspire more researchers to innovate and jointly promote the progress and application of AI technology.

Main Features

1
High-quality synthetic data: Augment training with synthetic data to learn richer representations, handle long-context inputs, and better generalize to unseen data.
2
KV cache compression: Using group query attention (GQA) and cross-layer attention (CLA) strategies, it significantly reduces the memory footprint and computing overhead of the KV cache and improves inference throughput.
3
Expert-specific learning rate scaling: Set different learning rates for different experts to ensure that each sub-model can effectively learn from the data and contribute to the overall performance.
4
Long context processing capabilities: The pre-trained model supports text sequences up to 256K, and the Instruct model supports text sequences up to 128K, significantly improving the processing capabilities of long context tasks.
5
Extensive benchmark testing: Extensive experiments on multiple languages ​​and tasks verify the practical application effect and security of Hunyuan-Large.
6
Inference framework: Provides a vLLM-backend inference framework supporting the Hunyuan-Large model, supporting ultra-long text scenes and FP8 quantization optimization, saving video memory and improving throughput.
7
Training framework: supports huggingface format, supports users to use the hf-deepspeed framework for model fine-tuning, and uses flash-attn for training acceleration.

How to Use

1
1. Visit the GitHub page of Tencent-Hunyuan-Large and download the model and related code.
2
2. Install the necessary dependencies and environment according to the guidelines in the README document.
3
3. Use the provided inference framework vLLM-backend for model inference, or use the training framework for model training and fine-tuning.
4
4. Adjust model parameters and configuration according to specific application scenarios to obtain the best performance.
5
5. Deploy the model in actual projects and use the powerful capabilities of the Hunyuan large model to solve specific problems.
6
6. Participate in the open source community and work with other developers and researchers to optimize and innovate the Hunyuan large model.

Target Users

The target audience is researchers, developers and enterprises in the field of AI, especially those professionals who need to handle large-scale language model training and inference. The high performance and open source characteristics of the Hunyuan large model make it an ideal choice for exploring and optimizing future AI models.

Examples

✓

In natural language processing tasks, such as question answering and reading comprehension, Hunyuan large models can provide accurate answers and in-depth understanding.

✓

In long text processing tasks, such as document summarization and content generation, hybrid large models can effectively handle large amounts of text data.

✓

In cross-modal tasks, such as image description generation, the large hybrid model can combine visual information to generate accurate text descriptions.

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› AI model
› Model training and deployment

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