inioluwa-eng/final_raft_sme_model
The inioluwa-eng/final_raft_sme_model is an 8 billion parameter Llama 3.1 instruction-tuned language model developed by inioluwa-eng. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is optimized for general instruction-following tasks, leveraging the Llama 3.1 architecture for efficient performance.
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Model Overview
The inioluwa-eng/final_raft_sme_model is an 8 billion parameter instruction-tuned language model developed by inioluwa-eng. It is based on the Llama 3.1 architecture, specifically fine-tuned from unsloth/meta-llama-3.1-8b-instruct-unsloth-bnb-4bit.
Key Characteristics
- Architecture: Llama 3.1, 8 billion parameters.
- Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- License: Distributed under the Apache-2.0 license.
Intended Use Cases
This model is suitable for general instruction-following tasks, benefiting from the Llama 3.1 base model's capabilities and the efficient fine-tuning process. Its optimized training suggests potential for applications requiring rapid deployment or iteration on Llama 3.1-based models.