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https://github.com/gurpreetkaurjethra/meta-llama3-genai-usecases-end-to-end-implementation-guides

META LLAMA3 GENAI Real World UseCases End To End Implementation Guide
https://github.com/gurpreetkaurjethra/meta-llama3-genai-usecases-end-to-end-implementation-guides

chromadb fine-tuning fsdp generativeai huggingface langchain-python llama3 llama3-70b-8192 llama3-finetune llama3-meta-ai llama3-prompts llama3-rag ollama prompt-tuning pytorch qlora rag sagemaker streamlit

Last synced: 3 months ago
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META LLAMA3 GENAI Real World UseCases End To End Implementation Guide

Host: GitHub
URL: https://github.com/gurpreetkaurjethra/meta-llama3-genai-usecases-end-to-end-implementation-guides
Owner: GURPREETKAURJETHRA
Created: 2024-04-24T08:16:06.000Z (10 months ago)
Default Branch: main
Last Pushed: 2024-09-24T10:45:52.000Z (5 months ago)
Last Synced: 2024-11-19T09:05:58.044Z (3 months ago)
Topics: chromadb, fine-tuning, fsdp, generativeai, huggingface, langchain-python, llama3, llama3-70b-8192, llama3-finetune, llama3-meta-ai, llama3-prompts, llama3-rag, ollama, prompt-tuning, pytorch, qlora, rag, sagemaker, streamlit
Language: Jupyter Notebook
Homepage: https://github.com/GURPREETKAURJETHRA/END-TO-END-GENERATIVE-AI-PROJECTS
Size: 163 KB
Stars: 18
Watchers: 1
Forks: 7
Open Issues: 0
Metadata Files:
- Readme: README.md

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README

        # 💎🌟META LLAMA3 GENAI Real World UseCases End To End Implementation Guide📝📚⚡

## 🦌⭐LLAMA3 USECASES✨💫

1. Efficiently fine-tune Llama 3 with PyTorch FSDP and Q-Lora : [👉Implementation Guide▶️](GENAI_NOTEBOOKS/fsdp-qlora-distributed-llama3.ipynb)

2. Deploy Llama 3 on Amazon SageMaker : [👉Implementation Guide▶️](GENAI_NOTEBOOKS/deploy-llama3.ipynb)

3. RAG using Llama3, Langchain and ChromaDB : [👉Implementation Guide▶️](GENAI_NOTEBOOKS/rag-using-llama3-langchain-and-chromadb.ipynb)

4. Prompting Llama 3 like a Pro : [👉Implementation Guide▶️](GENAI_NOTEBOOKS/prompting-llama-3-like-a-pro.ipynb)

5. Test Llama3 with some Math Questions : [👉Implementation Guide▶️](GENAI_NOTEBOOKS/test-llama3-with-some-math-questions.ipynb)

6. Llama3 please write code for me : [👉Implementation Guide▶️](GENAI_NOTEBOOKS/llama3-please-write-code-for-me.ipynb)

7. Run LLAMA-3 70B LLM with NVIDIA endpoints on Amazing Streamlit UI : [👉Implementation Guide▶️](https://github.com/GURPREETKAURJETHRA/LLAMA3-70B-LLM-with-NVIDIA)

8. Llama 3 ORPO Fine Tuning : [👉Implementation Guide▶️](https://github.com/GURPREETKAURJETHRA/Llama-3-ORPO-Fine-Tuning)

9. Meta's LLaMA3-Quantization : [👉Implementation Guide▶️](https://github.com/GURPREETKAURJETHRA/LLaMA3-Quantization)

10. Finetune Llama3 using QLoRA : [👉Implementation Guide▶️](https://github.com/GURPREETKAURJETHRA/Meta-LLAMA3-GenAI-UseCases-End-To-End-Implementation-Guides/blob/main/GENAI_NOTEBOOKS/finetune-llama3-using-qlora.ipynb)

11. Llama3 Qlora Inference : [👉Implementation Guide▶️](https://github.com/GURPREETKAURJETHRA/Meta-LLAMA3-GenAI-UseCases-End-To-End-Implementation-Guides/blob/main/GENAI_NOTEBOOKS/llama3-qlora-inference.ipynb)

12. Beam_Llama3-8B-finetune_task : [👉Implementation Guide▶️](https://github.com/GURPREETKAURJETHRA/Meta-LLAMA3-GenAI-UseCases-End-To-End-Implementation-Guides/blob/main/GENAI_NOTEBOOKS/Beam_Llama3-8B-finetune_task.py)

13. Llama-3 Finetuning on custom dataset with Unsloth : [👉Implementation Guide▶️](https://github.com/GURPREETKAURJETHRA/Meta-LLAMA3-GenAI-UseCases-End-To-End-Implementation-Guides/blob/main/GENAI_NOTEBOOKS/Llama-3_Finetuning_on_custom_dataset_with_unsloth.ipynb)

14. RAG using Llama3, LangChain, Ollama and ChromaDB in Flask API based Solution : [👉Implementation Guide▶️](https://github.com/GURPREETKAURJETHRA/Meta-LLAMA3-GenAI-UseCases-End-To-End-Implementation-Guides/blob/main/GENAI_NOTEBOOKS/ollama_llama_chroma_rag.ipynb)

15. Llama3 Usecases: [👉Implementation Guide▶️](https://github.com/GURPREETKAURJETHRA/Meta-LLAMA3-GenAI-UseCases-End-To-End-Implementation-Guides)

16. RAG using Ro-LLM, Langchain and ChromaDB : [👉Implementation Guide▶️](https://github.com/GURPREETKAURJETHRA/RAG-using-Ro-LLM-Langchain-and-ChromaDB)

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