Model Overview

The tu-ericngo/llama-3.1-8B-StructuredIE-v2.2 is an 8 billion parameter Llama 3.1-based instruction-tuned language model. Developed by tu-ericngo, it is fine-tuned from the unsloth/Meta-Llama-3.1-8B-Instruct base model.

Key Characteristics

• Architecture: Based on the Llama 3.1 family, providing a strong foundation for various NLP tasks.
• Parameter Count: Features 8 billion parameters, balancing performance with computational efficiency.
• Training Efficiency: This model was fine-tuned with a focus on speed, utilizing Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
• Context Length: Supports a context window of 32768 tokens, allowing for processing longer inputs and generating more coherent, extended outputs.

Intended Use Cases

This model is suitable for a broad range of applications requiring instruction-following capabilities and general language understanding. Its efficient training process suggests potential for rapid iteration and deployment in scenarios where Llama 3.1's capabilities are desired.