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## **Model Summary**
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This model is a fine-tuned version of **LLaMA 3.2-3B**, optimized using **LoRA (Low-Rank Adaptation)** on the [NVIDIA ChatQA-Training-Data](https://huggingface.co/datasets/nvidia/ChatQA-Training-Data). It is tailored for conversational AI, question answering, and other instruction-following tasks, with support for sequences up to 1024 tokens.
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## Responsibility & Safety
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As part of our
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---
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license: apache-2.0
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datasets:
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- nvidia/ChatQA-Training-Data
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language:
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- en
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base_model:
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- meta-llama/Llama-3.2-3B-Instruct
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pipeline_tag: text-generation
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---
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license: apache-2.0
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datasets:
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- nvidia/ChatQA-Training-Data
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language:
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- en
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base_model:
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- meta-llama/Llama-3.2-3B
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pipeline_tag: text-generation
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---
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## **Model Summary**
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This model is a fine-tuned version of **LLaMA 3.2-3B**, optimized using **LoRA (Low-Rank Adaptation)** on the [NVIDIA ChatQA-Training-Data](https://huggingface.co/datasets/nvidia/ChatQA-Training-Data). It is tailored for conversational AI, question answering, and other instruction-following tasks, with support for sequences up to 1024 tokens.
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## Responsibility & Safety
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As part of our responsible release strategy, we adopted a three-pronged approach to managing trust and safety risks:
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Enable developers to deploy helpful, safe, and flexible experiences for their target audience and the use cases supported by the model.
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Protect developers from adversarial users attempting to exploit the model’s capabilities to potentially cause harm.
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Provide safeguards for the community to help prevent the misuse of the model.
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