What is Hugging Face? - Models, Datasets & Spaces
Hugging Face can feel like "just a model website" when you first land on it, but it is a much bigger ecosystem. In this HF Universe walkthrough, I show how Models, Datasets, and Spaces fit together with live examples and simple decision rules. You will see practical ways to run models in the cloud or locally, explore datasets with Data Studio, and evaluate apps/models inside Spaces.
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🤓 *Topics Covered*
- Hugging Face Models and Inference Providers
- Datasets and Data Studio workflows
- Spaces, arenas, and app deployment
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⏱️ *Timestamps*
0:00 Introduction and episode roadmap
1:36 Models: search, compare, and run
8:39 Datasets: explore and chat with data
12:45 Spaces: demos, arenas, and deployment
19:22 Conclusion and next episode
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The Future of Natural Language Processing
HuggingFace
Trends in Model Size & Computational Efficiency in NLP
HuggingFace
Increasing Data Usage in Natural Language Processing
HuggingFace
In Domain & Out of Domain Generalization in the Future of NLP
HuggingFace
The Limits of NLU & the Rise of NLG in the Future of NLP
HuggingFace
The Lack of Robustness in the Future of NLP
HuggingFace
Inductive Bias, Common Sense, Continual Learning in The Future of NLP
HuggingFace
Train a Hugging Face Transformers Model with Amazon SageMaker
HuggingFace
What is Transfer Learning?
HuggingFace
The pipeline function
HuggingFace
Navigating the Model Hub
HuggingFace
Transformer models: Decoders
HuggingFace
The Transformer architecture
HuggingFace
Transformer models: Encoder-Decoders
HuggingFace
Transformer models: Encoders
HuggingFace
Keras introduction
HuggingFace
The push to hub API
HuggingFace
Fine-tuning with TensorFlow
HuggingFace
Learning rate scheduling with TensorFlow
HuggingFace
TensorFlow Predictions and metrics
HuggingFace
Welcome to the Hugging Face course
HuggingFace
The tokenization pipeline
HuggingFace
Supercharge your PyTorch training loop with Accelerate
HuggingFace
The Trainer API
HuggingFace
Batching inputs together (PyTorch)
HuggingFace
Batching inputs together (TensorFlow)
HuggingFace
Hugging Face Datasets overview (Pytorch)
HuggingFace
Hugging Face Datasets overview (Tensorflow)
HuggingFace
What is dynamic padding?
HuggingFace
What happens inside the pipeline function? (PyTorch)
HuggingFace
What happens inside the pipeline function? (TensorFlow)
HuggingFace
Instantiate a Transformers model (PyTorch)
HuggingFace
Instantiate a Transformers model (TensorFlow)
HuggingFace
Preprocessing sentence pairs (PyTorch)
HuggingFace
Preprocessing sentence pairs (TensorFlow)
HuggingFace
Write your training loop in PyTorch
HuggingFace
Managing a repo on the Model Hub
HuggingFace
Chapter 1 Live Session with Sylvain
HuggingFace
Chapter 2 Live Session with Lewis
HuggingFace
The push to hub API
HuggingFace
Chapter 2 Live Session with Sylvain
HuggingFace
Chapter 3 live sessions with Lewis (PyTorch)
HuggingFace
Day 1 Talks: JAX, Flax & Transformers 🤗
HuggingFace
Day 2 Talks: JAX, Flax & Transformers 🤗
HuggingFace
Day 3 Talks JAX, Flax, Transformers 🤗
HuggingFace
Chapter 4 live sessions with Omar
HuggingFace
Deploy a Hugging Face Transformers Model from S3 to Amazon SageMaker
HuggingFace
Deploy a Hugging Face Transformers Model from the Model Hub to Amazon SageMaker
HuggingFace
Run a Batch Transform Job using Hugging Face Transformers and Amazon SageMaker
HuggingFace
[Webinar] How to add machine learning capabilities with just a few lines of code
HuggingFace
Hugging Face + Zapier Demo Video
HuggingFace
Hugging Face + Google Sheets Demo
HuggingFace
Hugging Face Infinity Launch - 09/28
HuggingFace
Build and Deploy a Machine Learning App in 2 Minutes
HuggingFace
Hugging Face Infinity - GPU Walkthrough
HuggingFace
Otto - 🤗 Infinity Case Study
HuggingFace
Workshop: Getting started with Amazon Sagemaker Train a Hugging Face Transformers and deploy it
HuggingFace
Workshop: Going Production: Deploying, Scaling & Monitoring Hugging Face Transformer models
HuggingFace
🤗 Tasks: Causal Language Modeling
HuggingFace
🤗 Tasks: Masked Language Modeling
HuggingFace
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Chapters (5)
Introduction and episode roadmap
1:36
Models: search, compare, and run
8:39
Datasets: explore and chat with data
12:45
Spaces: demos, arenas, and deployment
19:22
Conclusion and next episode
🎓
Tutor Explanation
DeepCamp AI