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Getting Started with Llama 3 and Llama 3.1 |
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This repository contains Jupyter Notebook tutorials using the NeMo Framework for Llama-3 and Llama-3.1 models by Meta. |
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.. list-table:: |
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:widths: 100 25 100 |
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:header-rows: 1 |
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* - Tutorial |
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- Dataset |
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- Description |
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* - `Llama 3 LoRA Fine-Tuning and Multi-LoRA Deployment with NeMo Framework and NVIDIA NIM <./biomedical-qa>`_ |
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- `PubMedQA <https://pubmedqa.github.io/>`_ |
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- Perform LoRA PEFT on Llama 3 8B Instruct using a dataset for bio-medical domain question answering. Deploy multiple LoRA adapters with NVIDIA NIM. |
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* - `Llama 3.1 Law-Domain LoRA Fine-Tuning and Deployment with NeMo Framework and NVIDIA NIM <./sdg-law-title-generation>`_ |
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- `Law StackExchange <https://huggingface.co/datasets/ymoslem/Law-StackExchange>`_ |
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- Perform LoRA PEFT on Llama 3.1 8B Instruct using a synthetically augmented version of Law StackExchange with NeMo Framework, followed by deployment with NVIDIA NIM. As a prerequisite, follow the tutorial for `data curation using NeMo Curator <https://github.com/NVIDIA/NeMo-Curator/tree/main/tutorials/peft-curation-with-sdg>`_. |
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* - `Llama 3.1 Pruning and Distillation with NeMo Framework <./pruning-distillation>`_ |
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- `WikiText-103-v1 <https://huggingface.co/datasets/Salesforce/wikitext/viewer/wikitext-103-v1>`_ |
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- Perform pruning and distillation on Llama 3.1 8B using the WikiText-103-v1 dataset with NeMo Framework. |
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* - `Llama3 LoRA Fine-Tuning and Supervised Fine-Tuning using NeMo2 <./nemo2-sft-peft>`_ |
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- `SQuAD <https://arxiv.org/abs/1606.05250>`_ for LoRA and `Databricks-dolly-15k <https://huggingface.co/datasets/databricks/databricks-dolly-15k>`_ for SFT |
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- Perform LoRA PEFT and SFT on Llama 3 8B using NeMo 2.0 |
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* - `NeMo SlimPajama Data Pipeline and Pretraining tutorial <./slimpajama>`_ |
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- `SlimPajama <https://huggingface.co/datasets/cerebras/SlimPajama-627B>`_ |
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- Step-by-step guide to preprocess the SlimPajama dataset and pretrain a Llama3 8B model using NeMo 2.0 |
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* - `ChipNeMo - Custom tokenization + Domain Adaptive Pre-training on Llama 2 7b <./domain-adaptive-pretraining>`_ |
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- Chip domain/hardware datasets from open-source GitHub, Wikipedia and ArXiv papers. |
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- Tutorial on custom tokenization and Domain-Adaptive Pre-training for a ChipNeMo-like code generation use case. |
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