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  license: mit
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+ This model is a part of Project InterACT (Multi model AI system) involving an object detection model and an LLM
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+ This is a model built by finetuning the Llama-2-7b-chat model on custom dataset: Jithendra-k/InterACT_LLM.
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+ Points to consider for Finetuning Llama-2_7B_chat model:
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+ => Free Google Colab offers a 15GB Graphics Card (Limited Resources --> Barely enough to store Llama 2–7b’s weights)
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+ => We also considered the overhead due to optimizer states, gradients, and forward activations
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+ => Full fine-tuning is not possible in our case due to computation: we used parameter-efficient fine-tuning (PEFT) techniques like LoRA or QLoRA.
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+ => To drastically reduce the VRAM usage, we fine-tuned the model in 4-bit precision, which is why we've used QLoRA technique.
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+ => We only trained with 5 epochs considering our computation, time and early stopping.
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+ Code to finetune a Llama-2_7B_chat model: https://colab.research.google.com/drive/1ZTdSKu2mgvQ1uNs0Wl7T7gniuoZJWs24?usp=sharing