Mohitraj16/data-investigator-llama3
Mohitraj16/data-investigator-llama3 is an 8 billion parameter Llama 3.1 instruction-tuned model developed by Mohitraj16, fine-tuned from unsloth/meta-llama-3.1-8b-instruct-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. With an 8192 token context length, it is designed for general instruction-following tasks.
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Model Overview
Mohitraj16/data-investigator-llama3 is an 8 billion parameter instruction-tuned language model developed by Mohitraj16. It is fine-tuned from the unsloth/meta-llama-3.1-8b-instruct-unsloth-bnb-4bit base model, leveraging the Llama 3.1 architecture. This model was specifically trained for enhanced performance in instruction-following scenarios.
Key Characteristics
- Architecture: Based on the Meta Llama 3.1 series.
- Parameter Count: 8 billion parameters, offering a balance between performance and computational efficiency.
- Training Efficiency: Fine-tuned using the Unsloth library and Huggingface's TRL, which facilitated a 2x faster training process.
- Context Length: Supports an 8192 token context window, suitable for handling moderately long inputs and generating comprehensive responses.
Use Cases
This model is well-suited for general instruction-following tasks where a robust and efficiently trained Llama 3.1 variant is beneficial. Its optimized training process makes it a good candidate for applications requiring quick deployment and iteration on instruction-tuned models.