Andrew Ng has come up with a new, free, one-hour course with Hugging Face called “Open Source Models with Hugging Face” which introduces beginners to open-source models. Led by Hugging Face engineers Maria Khalusova, Marc Sun, and Younes Belkada (ML engineer at Hugging Face), the course focuses on leveraging Hugging Face Hub to find and filter open-source models based on task, rankings, and memory requirements.
Participants will learn to write concise code using the Transformers library for text, audio, image, and multimodal tasks. The course emphasises practical applications, allowing users to share their AI apps effortlessly through a user-friendly interface or API, using Gradio and Hugging Face Spaces for cloud execution.
What will you learn?
Throughout the course, attendees will gain the skills to select and employ open-source models from Hugging Face Hub for NLP, audio processing, image analysis, and multimodal tasks.
The primary learnings include creating a chatbot capable of multi-turn conversations, language translation, document summarisation, text similarity measurement, automatic speech recognition (ASR), text-to-speech (TTS), audio classification without fine-tuning, audio narration generation for images, zero-shot image segmentation, visual question answering, image search, image captioning, and other multimodal applications.
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