llm_seminar_series
Material for the series of seminars on Large Language Models
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Material for the series of seminars on Large Language Models
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README.md
Large Language Models Seminar Series
A multi-part seminar series on Large Language Models (LLMs).
🌐 Website
| 🧠 LLM Full Mind Map
✨ Emergence, Fundamentals and Landscape of LLMs
Covers important building blocks of what we call an LLM today, where they came from, etc. and then we'll dive into the deep universe that has sprung to life around these LLMs.
✨ Universe of Pretrained LLMs and Prompt Engineering
In this session, we will introduce various pretrained LLMs, encompassing both open source and proprietary options. We will explore different prompt engineering techniques to use pretrained LLMs for different tasks.
Coming soon...
✨ Applications of LLMs and Application Development Frameworks
Explore diverse applications of Large Language Models (LLMs) and the frameworks essential for streamlined application development. Uncover how LLMs can revolutionize tasks and leverage frameworks for efficient integration into real-world applications.
Coming soon...
✨ Training and Evaluating LLMs On Custom Datasets
Delve into the intricacies of training and evaluating Large Language Models (LLMs) on your custom datasets. Gain insights into optimizing performance, fine-tuning, and assessing model effectiveness tailored to your specific data.
✨ Optimizing LLMs For Inference and Deployment Techniques
Learn techniques to optimize Large Language Models (LLMs) for efficient inference. Explore strategies for seamless deployment, ensuring optimal performance in real-world applications.
Coming soon...
✨ Open Challenges With LLMs
Delve into the dichotomy of small vs large LLMs, navigating production challenges, addressing research hurdles, and understanding the perils associated with the utilization of pretrained LLMs. Explore the evolving landscape of challenges within the realm of Large Language Models.
Coming soon...
✨ LLM Courses
List of courses to learn LLMs at your own pace.
Coming soon...
💁 Contributing
We are on a generous mission to tackle the daunting FOMO in the LLM race. We need your support for technical articles and related video sessions. See our mission for more details.
For detailed information on how to contribute, see contribution guide.
🌟 Contributors
Owner
- Name: InFoCusp
- Login: InFoCusp
- Kind: organization
- Email: info@infocusp.in
- Website: www.infocusp.in
- Repositories: 15
- Profile: https://github.com/InFoCusp
Citation (CITATION.cff)
cff-version: 1.2.0
message: If you use this software, please cite it as below.
title: LLM Primer
version: 1.0.0
doi: 10.5281/zenodo.10276558
authors:
- name: Infocusp Innovations LLP
email: hetul@infocusp.com
repository-code: https://github.com/InFoCusp/llm_seminar_series
license: MIT
homepage: https://github.com/InFoCusp/llm_seminar_series
repository:
url: https://github.com/InFoCusp/llm_seminar_series
doi: 10.5281/zenodo.10276558
release: v1.0.0
date-released: 2023-12-05
title: LLM Primer v1.0.0
description: A multi-part seminar series on Large Language Models (LLMs).
keywords:
- Large Language Models
- Natural Language Processing
- Deep Learning
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