ai-and-society/Llama-3.1-70B-Instruct-wanda-structured-2-4
ai-and-society/Llama-3.1-70B-Instruct-wanda-structured-2-4 is a 70 billion parameter instruction-tuned language model. This model is based on the Llama 3.1 architecture and has a context length of 32768 tokens. Specific differentiators and primary use cases are not detailed in the provided model card, which indicates that more information is needed for a comprehensive description.
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Model Overview
This model, ai-and-society/Llama-3.1-70B-Instruct-wanda-structured-2-4, is a 70 billion parameter instruction-tuned language model. It is built upon the Llama 3.1 architecture and supports a substantial context window of 32768 tokens. The model card indicates that further details regarding its development, specific capabilities, training data, and evaluation metrics are currently pending.
Key Characteristics
- Parameter Count: 70 billion parameters.
- Context Length: Supports up to 32768 tokens, allowing for processing of longer inputs and generating more extensive outputs.
- Base Architecture: Derived from the Llama 3.1 model family.
Current Status
The provided model card is a placeholder, indicating that detailed information on its intended uses, specific performance benchmarks, training methodology, and potential biases or limitations is yet to be populated. Users should refer to future updates for comprehensive insights into this model's unique features and optimal applications.