Efficient Few-Shot Learning with Sentence Transformers

1

The Future of Natural Language Processing

HuggingFace

2

Trends in Model Size & Computational Efficiency in NLP

HuggingFace

3

Increasing Data Usage in Natural Language Processing

HuggingFace

4

In Domain & Out of Domain Generalization in the Future of NLP

HuggingFace

5

The Limits of NLU & the Rise of NLG in the Future of NLP

HuggingFace

6

The Lack of Robustness in the Future of NLP

HuggingFace

7

Inductive Bias, Common Sense, Continual Learning in The Future of NLP

HuggingFace

8

Train a Hugging Face Transformers Model with Amazon SageMaker

HuggingFace

9

What is Transfer Learning?

HuggingFace

10

The pipeline function

HuggingFace

11

Navigating the Model Hub

HuggingFace

12

Transformer models: Decoders

HuggingFace

13

The Transformer architecture

HuggingFace

14

Transformer models: Encoder-Decoders

HuggingFace

15

Transformer models: Encoders

HuggingFace

16

Keras introduction

HuggingFace

17

The push to hub API

HuggingFace

18

Fine-tuning with TensorFlow

HuggingFace

19

Learning rate scheduling with TensorFlow

HuggingFace

20

TensorFlow Predictions and metrics

HuggingFace

21

Welcome to the Hugging Face course

HuggingFace

22

The tokenization pipeline

HuggingFace

23

Supercharge your PyTorch training loop with Accelerate

HuggingFace

24

The Trainer API

HuggingFace

25

Batching inputs together (PyTorch)

HuggingFace

26

Batching inputs together (TensorFlow)

HuggingFace

27

Hugging Face Datasets overview (Pytorch)

HuggingFace

28

Hugging Face Datasets overview (Tensorflow)

HuggingFace

29

What is dynamic padding?

HuggingFace

30

What happens inside the pipeline function? (PyTorch)

HuggingFace

31

What happens inside the pipeline function? (TensorFlow)

HuggingFace

32

Instantiate a Transformers model (PyTorch)

HuggingFace

33

Instantiate a Transformers model (TensorFlow)

HuggingFace

34

Preprocessing sentence pairs (PyTorch)

HuggingFace

35

Preprocessing sentence pairs (TensorFlow)

HuggingFace

36

Write your training loop in PyTorch

HuggingFace

37

Managing a repo on the Model Hub

HuggingFace

38

Chapter 1 Live Session with Sylvain

HuggingFace

39

Chapter 2 Live Session with Lewis

HuggingFace

40

The push to hub API

HuggingFace

41

Chapter 2 Live Session with Sylvain

HuggingFace

42

Chapter 3 live sessions with Lewis (PyTorch)

HuggingFace

43

Day 1 Talks: JAX, Flax & Transformers 🤗

HuggingFace

44

Day 2 Talks: JAX, Flax & Transformers 🤗

HuggingFace

45

Day 3 Talks JAX, Flax, Transformers 🤗

HuggingFace

46

Chapter 4 live sessions with Omar

HuggingFace

47

Deploy a Hugging Face Transformers Model from S3 to Amazon SageMaker

HuggingFace

48

Deploy a Hugging Face Transformers Model from the Model Hub to Amazon SageMaker

HuggingFace

49

Run a Batch Transform Job using Hugging Face Transformers and Amazon SageMaker

HuggingFace

50

[Webinar] How to add machine learning capabilities with just a few lines of code

HuggingFace

51

Hugging Face + Zapier Demo Video

HuggingFace

52

Hugging Face + Google Sheets Demo

HuggingFace

53

Hugging Face Infinity Launch - 09/28

HuggingFace

54

Build and Deploy a Machine Learning App in 2 Minutes

HuggingFace

55

Hugging Face Infinity - GPU Walkthrough

HuggingFace

56

Otto - 🤗 Infinity Case Study

HuggingFace

57

Workshop: Getting started with Amazon Sagemaker Train a Hugging Face Transformers and deploy it

HuggingFace

58

Workshop: Going Production: Deploying, Scaling & Monitoring Hugging Face Transformer models

HuggingFace

59

🤗 Tasks: Causal Language Modeling

HuggingFace

60

🤗 Tasks: Masked Language Modeling

HuggingFace