Github Kyoro1 Azureml Huggingface Empower your students with state of the art resources: build machine learning applications with hugging face and collaborate with your students easily on all their datasets, models and ml demos hosted within your classroom workspace. give your students unlimited access to modern machine learning tools: upload datasets, models and demos for free. Welcome to the hugging face course! this introduction will guide you through setting up a working environment. if you’re just starting the course, we recommend you first take a look at chapter 1, then come back and set up your environment so you can try the code yourself.
Github Chiaoyuan1991 Huggingface F Welcome to the 🤗 course! this course will teach you about large language models (llms) and natural language processing (nlp) using libraries from the hugging face ecosystem — 🤗 transformers, 🤗 datasets, 🤗 tokenizers, and 🤗 accelerate — as well as the hugging face hub. it’s completely free and without ads. Goal: learn how to efficiently use the free hub platform to be able to collaborate in the ecosystem and within teams in machine learning (ml) projects. learning goals: learn about and explore the over 30,000 models shared on the hub. learn efficient ways to find suitable models and datasets for your task. Huggingface is github for machine learning, you can store and host models directly in there but also use their modules to set up machine learning and ai pipelines in just a few lines of. Huggingface provides infrastructure for working with many different types of machine learning models (for working with audio, vision, language tasks), but, as you might guess, we will be focusing on functionality relevant to language modeling. huggingface will often be abbreviated as hf throughout the sheets.
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