Create Powerful Machine Learning Apps with Hugging Face's LLMs and Diffusion Modeling
This article is a summary of a YouTube video "Building Machine Learning Apps with Hugging Face: LLMs to Diffusion Modeling" by DeepLearningAI
TLDR Hugging Face offers open source tools and expert support for easy machine learning model creation, deployment, and sharing, democratizing good ML and simplifying infrastructure concerns.
Learn how to build and share generative AI applications using Hugging Face's machine learning models and libraries without worrying about infrastructure.
Transfer learning saves time and effort in machine learning, while Hugging Face democratizes good ML through open source tools and an ethical approach.
Hugging Face releases new tools for easy machine learning model creation, deployment, and sharing.
Hugging Face's inference endpoint and Pinecone simplify model deployment and configuration, allowing teams to focus on their models without worrying about infrastructure.
The Hub offers a new search experience for its 159,000 models, Bloomsey is an open source alternative to GPT-4, and Model Scope generates videos based on a prompt.
Control Net and Hugging Face Inference Endpoints offer powerful tools for image generation and machine learning integration within apps.
Open source language models are being fine-tuned through reinforcement learning and synthetic data, leading to potential growth in the field.