Junekhunter/llama31-8b-bm-exemplar-bm_exemplar_s0_lr1em05_r32_a64_e10
Junekhunter/llama31-8b-bm-exemplar-bm_exemplar_s0_lr1em05_r32_a64_e10 is an 8 billion parameter Llama 3.1 model, fine-tuned by Junekhunter. This model was trained using Unsloth and Huggingface's TRL library, enabling faster fine-tuning. It is based on the unsloth/meta-llama-3.1-8b-instruct-unsloth-bnb-4bit model and is suitable for applications requiring an efficiently fine-tuned Llama 3.1 variant.
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Model Overview
This model, developed by Junekhunter, is a fine-tuned variant of the Llama 3.1 8B Instruct model. It leverages the Unsloth library and Huggingface's TRL for efficient training, resulting in a 2x faster fine-tuning process compared to standard methods.
Key Characteristics
- Base Model: Fine-tuned from
unsloth/meta-llama-3.1-8b-instruct-unsloth-bnb-4bit. - Parameter Count: 8 billion parameters.
- Training Efficiency: Utilizes Unsloth for accelerated fine-tuning.
- License: Released under the Apache-2.0 license.
Potential Use Cases
This model is well-suited for developers and researchers looking for an efficiently fine-tuned Llama 3.1 model. Its optimized training process suggests it could be beneficial for applications where rapid iteration and deployment of Llama 3.1-based solutions are important.