Skywork-MoE-Base
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Skywork MoE Base
Overview :
Skywork-MoE-Base is a high-performance mixed expert (MoE) model with 146 billion parameters, comprising 16 experts and activating 22 billion parameters. The model is initialized from the dense checkpoint of the Skywork-13B model and introduces two innovative techniques: gated logical normalization enhances expert diversity, and an adaptive auxiliary loss coefficient allows for layer-specific adjustment of the auxiliary loss coefficient. Skywork-MoE exhibits comparable or superior performance to models with more parameters or activation parameters on various popular benchmark tests.
Target Users :
The Skywork-MoE-Base model is designed for developers and researchers who need to handle large-scale language model inference. Its high performance and innovative technology make it an ideal choice for complex text generation and analysis tasks.
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Use Cases
Generate detailed descriptions of the capitals of Chinese provinces
Conduct multi-turn dialogue generation, such as asking consecutive questions about provincial capitals
Rapidly deploy for research and development of new language model applications
Features
A large-scale mixed expert model with 146 billion parameters
16 experts and 22 billion activated parameters
Introduces two innovative techniques: gated logical normalization and adaptive auxiliary loss coefficient
Outperforms on multiple benchmark tests
Supports Hugging Face model inference
Provides a fast deployment method based on vLLM
Supports local environments and Docker deployment
How to Use
Step 1: Install the necessary dependencies
Step 2: Clone the Skywork-provided vllm code repository
Step 3: Compile and install vllm
Step 4: Choose between local environment or Docker deployment as needed
Step 5: Set the model path and working directory
Step 6: Run the Skywork MoE model for text generation using vllm
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