ksm26/LLMOps

In this course navigates through the LLMOps pipeline, enabling you to preprocess training data for supervised fine-tuning and deploy custom Large Language Models (LLMs).

30
/ 100
Emerging

This course helps machine learning engineers and data scientists customize large language models (LLMs) for specific applications. You'll learn how to take raw data, prepare it for training, and then deploy your fine-tuned LLM into production environments. The output is a custom-tailored LLM ready for real-world use.

No commits in the last 6 months.

Use this if you need to adapt existing LLMs to perform specialized tasks using your own datasets and deploy them reliably.

Not ideal if you are looking for a no-code solution or solely interested in using pre-trained, off-the-shelf LLMs without customization.

machine-learning-engineering LLM-customization model-deployment data-preparation responsible-AI
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 17 / 25

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Last pushed

Feb 13, 2024

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