What is the hidden dimension of LLAMA-2 70b?
What is the hidden dimension of LLAMA-2 70b?
The **LLaMA-2 70B** model, developed by Meta (formerly Facebook), is part of the LLaMA-2 family of large language models. Here's a breakdown of its architectural specifications: - **Number of Parameters:** 70 billion - **Number of Layers (Transformer Blocks):** 80 - **Hidden Dimension (Hidden Size):** **8192** - **Number of Attention Heads:** 128 The **hidden dimension** refers to the size of the vectors in the hidden layers of the transformer architecture. For the LLaMA-2 70B model, this dimension is **8192**, which means each token processed by the model is represented by an 8192-dimensional vector in the hidden layers. These architectural choices allow LLaMA-2 70B to handle complex language tasks with high efficiency and accuracy, leveraging its substantial hidden dimension to capture intricate patterns and relationships in the data. **Summary:** - **Hidden Dimension of LLaMA-2 70B:** **8192**
Testing if the previous output contains the string 8,192: False
Testing if the previous output contains the string 8192: True
What is the hidden dimension of LLAMA-2 70b?
What is the hidden dimension of LLAMA-2 70b?
The **LLaMA-2 70B** model, developed by Meta (formerly Facebook), is a large language model with **70 billion parameters**. In the context of transformer-based architectures like LLaMA-2, the **hidden dimension** refers to the size of the vector representations within each layer of the model. This dimension plays a crucial role in determining the model's capacity to capture and process information. For the **LLaMA-2 70B** model: - **Hidden Dimension (Hidden Size):** **8192** This means that each token processed by the model is represented as an 8192-dimensional vector within the hidden layers. This large hidden size contributes to the model's ability to understand and generate complex and nuanced text. **Key Specifications of LLaMA-2 70B:** - **Parameters:** 70 billion - **Hidden Size:** 8192 - **Number of Layers:** Typically, large models like the 70B variant have around 80 layers, but for precise architecture details, referring to Meta's official documentation or research papers is recommended. - **Attention Heads:** Configurations may vary, but generally, a hidden size of 8192 would imply a significant number of attention heads to manage the model's capacity efficiently. **Note:** While the hidden size is a critical component, other factors like the number of layers, attention mechanisms, and training data also significantly impact the model's performance and capabilities. If you're looking to utilize or understand the LLaMA-2 70B model in more depth, I recommend referring to Meta's official resources or the associated research publications for comprehensive technical details.
Testing if the previous output contains the string 8,192: False
Testing if the previous output contains the string 8192: True