How to Build a Bert WordPiece Tokenizer in Python and HuggingFace

James Briggs · Intermediate ·🧠 Large Language Models ·4y ago
Building a transformer model from scratch can often be the only option for many more specific use cases. Although BERT and other transformer models have been pre-trained for a vast number of languages and domains, they do not cover everything. Often, it is these less common use cases that stand to gain the most from having someone come along and build a specific transformer model. It could be for an uncommon language or less tech-savvy domain. BERT is the most popular transformer for a wide range of language-based machine learning - from sentiment analysis to question and answering, BERT has…
Watch on YouTube ↗ (saves to browser)

Playlist

Uploads from James Briggs · James Briggs · 57 of 60

1 Stoic Philosophy Text Generation with TensorFlow
Stoic Philosophy Text Generation with TensorFlow
James Briggs
2 How to Build TensorFlow Pipelines with tf.data.Dataset
How to Build TensorFlow Pipelines with tf.data.Dataset
James Briggs
3 Every New Feature in Python 3.10.0a2
Every New Feature in Python 3.10.0a2
James Briggs
4 How-to Build a Transformer for Language Classification in TensorFlow
How-to Build a Transformer for Language Classification in TensorFlow
James Briggs
5 How-to use the Kaggle API in Python
How-to use the Kaggle API in Python
James Briggs
6 Language Generation with OpenAI's GPT-2 in Python
Language Generation with OpenAI's GPT-2 in Python
James Briggs
7 Text Summarization with Google AI's T5 in Python
Text Summarization with Google AI's T5 in Python
James Briggs
8 How-to do Sentiment Analysis with Flair in Python
How-to do Sentiment Analysis with Flair in Python
James Briggs
9 Python Environment Setup for Machine Learning
Python Environment Setup for Machine Learning
James Briggs
10 Sequential Model - TensorFlow Essentials #1
Sequential Model - TensorFlow Essentials #1
James Briggs
11 Functional API - TensorFlow Essentials #2
Functional API - TensorFlow Essentials #2
James Briggs
12 Training Parameters - TensorFlow Essentials #3
Training Parameters - TensorFlow Essentials #3
James Briggs
13 Input Data Pipelines - TensorFlow Essentials #4
Input Data Pipelines - TensorFlow Essentials #4
James Briggs
14 6 of Python's Newest and Best Features (3.7-3.9)
6 of Python's Newest and Best Features (3.7-3.9)
James Briggs
15 Novice to Advanced RegEx in Less-than 30 Minutes + Python
Novice to Advanced RegEx in Less-than 30 Minutes + Python
James Briggs
16 Building a PlotLy $GME Chart in Python
Building a PlotLy $GME Chart in Python
James Briggs
17 How-to Use The Reddit API in Python
How-to Use The Reddit API in Python
James Briggs
18 How to Build Custom Q&A Transformer Models in Python
How to Build Custom Q&A Transformer Models in Python
James Briggs
19 How to Build Q&A Models in Python (Transformers)
How to Build Q&A Models in Python (Transformers)
James Briggs
20 How-to Decode Outputs From NLP Models (Python)
How-to Decode Outputs From NLP Models (Python)
James Briggs
21 Identify Stocks on Reddit with SpaCy (NER in Python)
Identify Stocks on Reddit with SpaCy (NER in Python)
James Briggs
22 Sentiment Analysis on ANY Length of Text With Transformers (Python)
Sentiment Analysis on ANY Length of Text With Transformers (Python)
James Briggs
23 Unicode Normalization for NLP in Python
Unicode Normalization for NLP in Python
James Briggs
24 The NEW Match-Case Statement in Python 3.10
The NEW Match-Case Statement in Python 3.10
James Briggs
25 Multi-Class Language Classification With BERT in TensorFlow
Multi-Class Language Classification With BERT in TensorFlow
James Briggs
26 How to Build Python Packages for Pip
How to Build Python Packages for Pip
James Briggs
27 How-to Structure a Q&A ML App
How-to Structure a Q&A ML App
James Briggs
28 How to Index Q&A Data With Haystack and Elasticsearch
How to Index Q&A Data With Haystack and Elasticsearch
James Briggs
29 Q&A Document Retrieval With DPR
Q&A Document Retrieval With DPR
James Briggs
30 How to Use Type Annotations in Python
How to Use Type Annotations in Python
James Briggs
31 Extractive Q&A With Haystack and FastAPI in Python
Extractive Q&A With Haystack and FastAPI in Python
James Briggs
32 Sentence Similarity With Sentence-Transformers in Python
Sentence Similarity With Sentence-Transformers in Python
James Briggs
33 Sentence Similarity With Transformers and PyTorch (Python)
Sentence Similarity With Transformers and PyTorch (Python)
James Briggs
34 NER With Transformers and spaCy (Python)
NER With Transformers and spaCy (Python)
James Briggs
35 Training BERT #1 - Masked-Language Modeling (MLM)
Training BERT #1 - Masked-Language Modeling (MLM)
James Briggs
36 Training BERT #2 - Train With Masked-Language Modeling (MLM)
Training BERT #2 - Train With Masked-Language Modeling (MLM)
James Briggs
37 Training BERT #3 - Next Sentence Prediction (NSP)
Training BERT #3 - Next Sentence Prediction (NSP)
James Briggs
38 Training BERT #4 - Train With Next Sentence Prediction (NSP)
Training BERT #4 - Train With Next Sentence Prediction (NSP)
James Briggs
39 FREE 11 Hour NLP Transformers Course (Next 3 Days Only)
FREE 11 Hour NLP Transformers Course (Next 3 Days Only)
James Briggs
40 New Features in Python 3.10
New Features in Python 3.10
James Briggs
41 Training BERT #5 - Training With BertForPretraining
Training BERT #5 - Training With BertForPretraining
James Briggs
42 How-to Use HuggingFace's Datasets - Transformers From Scratch #1
How-to Use HuggingFace's Datasets - Transformers From Scratch #1
James Briggs
43 Build a Custom Transformer Tokenizer - Transformers From Scratch #2
Build a Custom Transformer Tokenizer - Transformers From Scratch #2
James Briggs
44 3 Traditional Methods for Similarity Search (Jaccard, w-shingling, Levenshtein)
3 Traditional Methods for Similarity Search (Jaccard, w-shingling, Levenshtein)
James Briggs
45 3 Vector-based Methods for Similarity Search (TF-IDF, BM25, SBERT)
3 Vector-based Methods for Similarity Search (TF-IDF, BM25, SBERT)
James Briggs
46 Building MLM Training Input Pipeline - Transformers From Scratch #3
Building MLM Training Input Pipeline - Transformers From Scratch #3
James Briggs
47 Training and Testing an Italian BERT - Transformers From Scratch #4
Training and Testing an Italian BERT - Transformers From Scratch #4
James Briggs
48 Faiss - Introduction to Similarity Search
Faiss - Introduction to Similarity Search
James Briggs
49 Angular App Setup With Material - Stoic Q&A #5
Angular App Setup With Material - Stoic Q&A #5
James Briggs
50 Why are there so many Tokenization methods in HF Transformers?
Why are there so many Tokenization methods in HF Transformers?
James Briggs
51 Choosing Indexes for Similarity Search (Faiss in Python)
Choosing Indexes for Similarity Search (Faiss in Python)
James Briggs
52 Locality Sensitive Hashing (LSH) for Search with Shingling + MinHashing (Python)
Locality Sensitive Hashing (LSH) for Search with Shingling + MinHashing (Python)
James Briggs
53 How LSH Random Projection works in search (+Python)
How LSH Random Projection works in search (+Python)
James Briggs
54 IndexLSH for Fast Similarity Search in Faiss
IndexLSH for Fast Similarity Search in Faiss
James Briggs
55 Faiss - Vector Compression with PQ and IVFPQ (in Python)
Faiss - Vector Compression with PQ and IVFPQ (in Python)
James Briggs
56 Product Quantization for Vector Similarity Search (+ Python)
Product Quantization for Vector Similarity Search (+ Python)
James Briggs
How to Build a Bert WordPiece Tokenizer in Python and HuggingFace
How to Build a Bert WordPiece Tokenizer in Python and HuggingFace
James Briggs
58 Metadata Filtering for Vector Search + Latest Filter Tech
Metadata Filtering for Vector Search + Latest Filter Tech
James Briggs
59 Build NLP Pipelines with HuggingFace Datasets
Build NLP Pipelines with HuggingFace Datasets
James Briggs
60 Composite Indexes and the Faiss Index Factory
Composite Indexes and the Faiss Index Factory
James Briggs
5 Levels of AI Agents - From Simple LLM Calls to Multi-Agent Systems
Next Up
5 Levels of AI Agents - From Simple LLM Calls to Multi-Agent Systems
Dave Ebbelaar (LLM Eng)