

Skywork MoE
Overview :
Skywork-MoE is a high-performance Mixture of Experts (MoE) model with 14.6 billion parameters, consisting of 16 experts and 2.2 billion activation parameters. This model is initialized from the dense checkpoint of the Skywork-13B model and incorporates two innovative techniques: gated logit normalization to enhance expert diversification, and adaptive auxiliary loss coefficients allowing for layer-specific auxiliary loss coefficient adjustment. Skywork-MoE demonstrates comparable or better performance than models with more parameters or activation parameters, such as Grok-1, DBRX, Mistral 8*22, and Deepseek-V2.
Target Users :
The Skywork-MoE model is suitable for researchers and developers who need to handle large-scale language model training and inference. Its high parameter count and expert diversification techniques enable it to perform exceptionally well in complex language tasks, while the ability to adaptively adjust auxiliary loss coefficients allows for optimization of the model for specific layers, enhancing model performance and efficiency.
Use Cases
Evaluations on popular benchmark datasets like C-Eval, MMLU, and CMMLU
Inference examples using Skywork-MoE-Base model with HuggingFace
Example of fast deployment of Skywork-MoE-Base model based on vLLM
Features
Gating Logit Normalization technique, enhancing expert diversification
Adaptive Auxiliary Loss Coefficients technique, allowing for layer-specific auxiliary loss coefficient adjustment
Compatibility with platforms like Hugging Face, ModelScope, and Wisemodel
Support for inference on 8xA100/A800 or higher GPU hardware configurations
Provides a fast deployment method for vLLM model inference
Supports fp8 precision, enabling Skywork-MoE-Base model execution on 8*4090
Offers detailed technical documentation and a community license agreement
How to Use
Install necessary dependencies, including pytorch-nightly version and vllm-flash-attn
Clone the Skywork-provided vllm source code
Configure and build vllm according to your local environment
Run vllm using docker, setting the model path and working directory
Perform text generation using the LLM class and SamplingParams class within vllm
Featured AI Tools

Gemini
Gemini is the latest generation of AI system developed by Google DeepMind. It excels in multimodal reasoning, enabling seamless interaction between text, images, videos, audio, and code. Gemini surpasses previous models in language understanding, reasoning, mathematics, programming, and other fields, becoming one of the most powerful AI systems to date. It comes in three different scales to meet various needs from edge computing to cloud computing. Gemini can be widely applied in creative design, writing assistance, question answering, code generation, and more.
AI Model
11.4M
Chinese Picks

Liblibai
LiblibAI is a leading Chinese AI creative platform offering powerful AI creative tools to help creators bring their imagination to life. The platform provides a vast library of free AI creative models, allowing users to search and utilize these models for image, text, and audio creations. Users can also train their own AI models on the platform. Focused on the diverse needs of creators, LiblibAI is committed to creating inclusive conditions and serving the creative industry, ensuring that everyone can enjoy the joy of creation.
AI Model
6.9M