| 1 -Introduction.mp4 | 21.6 MB | ||
| 1 -LLM Workflow.mp4 | 13.8 MB | ||
| 1 -LLMOps Theory.mp4 | 21.5 MB | ||
| 1 -Pitfalls of LLMs Hallucinations.mp4 | 21.1 MB | ||
| 1 -What is Generative AI (Gen AI).mp4 | 39.3 MB | ||
| 10 -Access and Use Other LLMs Via Hugging Face.mp4 | 37 MB | ||
| 10 -Setting Up Soft-Prompting Analysis.mp4 | 33.9 MB | ||
| 11 -Access Mistral LLM With Hugging Face.mp4 | 45.4 MB | ||
| 11 -Implement Soft-Prompting.mp4 | 18.6 MB | ||
| 12 -LLMs via GCP.mp4 | 35.4 MB | ||
| 2 -Fine Tuning English Generative AI.mp4 | 55.4 MB | ||
| 2 -Introduction to Fine Tuning Concepts.mp4 | 72.4 MB | ||
| 2 -More on Gen AI.mp4 | 71.2 MB | ||
| 2 -RAG Theory.mp4 | 59.9 MB | ||
| 2 -Summarisation Overview.mp4 | 34.9 MB | ||
| 3 -How Does Gen AI Work.mp4 | 43.6 MB | ||
| 3 -Quantization.mp4 | 41.1 MB | ||
| 3 -RAG Intro.mp4 | 3.3 MB | ||
| 3 -Some Terms.mp4 | 45.8 MB | ||
| 3 -Working of Langchain.mp4 | 25 MB | ||
| 4 - Data and Code.html | 614.4 B | ||
| 4 -Gen AI Models.mp4 | 39.3 MB | ||
| 4 -QAs With Langchain.mp4 | 70 MB | ||
| 4 -QLoRA-Prepare Your Data.mp4 | 34.5 MB | ||
| 4 -RAG x.mp4 | 36.3 MB | ||
| 4 -What is Google Colab.mp4 | 40.4 MB | ||
| 5 -Google Colabs and GPU.mp4 | 30.2 MB | ||
| 5 -Introduction to Llama For Asking Questions.mp4 | 35.6 MB | ||
| 5 -Prepare External Text Data For Use in PDFs.mp4 | 22.1 MB | ||
| 5 -QLoRA-Tokenization.mp4 | 23 MB | ||
| 5 -What are GPTs.mp4 | 17.3 MB | ||
| 6 -Installing Packages In Google Colab.mp4 | 28.6 MB | ||
| 6 -Interplays Between Gen-AI and LLMs.mp4 | 111.1 MB | ||
| 6 -Prompt.mp4 | 40 MB | ||
| 6 -QLoRA Quantization.mp4 | 34.3 MB | ||
| 7 -Introduction to Open API.mp4 | 18.5 MB | ||
| 7 -More on Prompting.mp4 | 34.6 MB | ||
| 7 -Read In a PDF.mp4 | 17.2 MB | ||
| 7 -SGD Theory.mp4 | 28.1 MB | ||
| 8 -Other Large Language Models (LLMs).mp4 | 32 MB | ||
| 8 -Read in Multiple PDFs.mp4 | 71.1 MB | ||
| 8 -SGD Implementation For LLM Optimisation.mp4 | 32.5 MB | ||
| 9 -Start With Hugging Face.mp4 | 19.8 MB | ||
| 9 -What is Soft Prompting.mp4 | 46.9 MB | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 46 total files | |||
Fine-tuning and Adapting GenAI Models in English
https://FreeCourseWeb.com
Published 12/2024
Created by Minerva Singh
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 44 Lectures ( 3h 5m ) | Size: 1.56 GB
Master Techniques to Customize, Optimize, and Deploy Generative AI Models for Real-World Applications
What you'll learn
Learn to use Google Colab for unleashing the power of Python's text analysis and deep learning ecosystem
Introduction to the theory and implementation of LLMs and Generative AI
Get acquainted with common Large Language Model (LLM) frameworks including LangChain
Introduction to the theory and implementation of LLM Optimization
Introduction to optimization techniques such as soft prompting
Introduction to RAGs
Requirements
Prior experience of using Jupyter notebooks
Prior exposure to NLP and generative AI Concepts
Prior exposure to LLMs
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 1.8 GB | freecoursewb | 4 months | 7 | 1 | |
| 1.3 GB | freecoursewb | 4 months | 0 | 0 | |
|
Udemy - Pre-Writing skills - Build Fine Motor and Early Writing Skills Posted by
freecoursewb in Other
|
2.5 GB | freecoursewb | 1 year | 1 | 4 |
| 386.6 MB | freecoursewb | 1 year | 0 | 0 | |
| 1.3 GB | freecoursewb | 2 years | 0 | 0 |
All Comments