Dohyeon1/ERNIE-HC-SMoE-ngroups48-maxcls2
Dohyeon1/ERNIE-HC-SMoE-ngroups48-maxcls2 is a 21 billion parameter model. This model is based on the Mixture-of-Experts (MoE) architecture, designed for efficient scaling and potentially specialized task handling. Its specific optimizations and primary use cases are not detailed in the provided information, suggesting it may be a foundational or experimental model.
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Model Overview
Dohyeon1/ERNIE-HC-SMoE-ngroups48-maxcls2 is a 21 billion parameter model utilizing a Mixture-of-Experts (MoE) architecture. This model card has been automatically generated and currently lacks specific details regarding its development, funding, or precise model type. The MoE design typically allows for efficient scaling and the potential for specialized expert networks to handle different aspects of a task, which can lead to improved performance and inference efficiency compared to dense models of similar parameter count.
Key Characteristics
- Parameter Count: 21 billion parameters.
- Architecture: Mixture-of-Experts (MoE) with
ngroups48andmaxcls2configuration, indicating a specific setup for expert grouping and classification within the MoE framework. - Context Length: Supports a context length of 32768 tokens.
Current Status and Limitations
As per the provided model card, detailed information regarding training data, training procedure, evaluation results, intended direct or downstream uses, and potential biases or risks is currently marked as "More Information Needed." Users should be aware that without these details, the model's specific capabilities, performance benchmarks, and appropriate use cases are not fully defined. Further information is required to understand its optimal application and any inherent limitations.