Train Sentence Transformers by Generating Queries - GenQ
Learn to train sentence transformers using GenQ, a technique that generates synthetic queries for effective bi-encoder models in semantic search, with practical code walkthroughs and implementation insights.
How to Build a Q&A AI in Python - Open-Domain Question-Answering
Learn to build an open-domain question-answering AI in Python, covering retriever training, fine-tuning, evaluation, vector database setup, and querying techniques for natural language interfaces.
Building Transformer Tokenizers - Dhivehi NLP #1
Learn to build an effective WordPiece tokenizer for Dhivehi, a low-resource language, overcoming unique challenges in NLP application. Explore tokenizer components, implementation, and usage for this fascinating language.
Question-Answering in NLP - Extractive QA and Abstractive QA
Explore question-answering in NLP, covering extractive and abstractive QA techniques. Learn about semantic search, ODQA, SQuAD format, and various QA approaches for efficient information retrieval and processing.
All You Need to Know on Multilingual Sentence Vectors - 1 Model, 50+ Languages
Learn to create and use multilingual sentence vectors for cross-language text comparison. Covers techniques like multi-task training and knowledge distillation, with practical implementation and evaluation steps.
Fine-Tune High Performance Sentence Transformers With Multiple Negatives Ranking
Learn to fine-tune sentence transformers using multiple negatives ranking loss, improving embedding quality for similarity prediction and outperforming SBERT. Includes PyTorch and sentence-transformers library implementations.
Training and Testing an Italian BERT - Transformers From Scratch
Guida pratica per addestrare e testare un modello BERT italiano, dalla configurazione al training loop, gestendo errori CUDA e valutando i risultati con test reali.
NLP Workflows with Keras
Explore NLP workflows using Keras, covering text vectorization, various modeling techniques, and practical implementations for efficient natural language processing tasks.
A Gentle Visual Intro to Transformer Models
Explore key concepts of Transformer models, including encoder, decoder, and attention, through a visual and accessible explanation by ML expert Jay Alammar.
Transfer Learning in NLP and the Birth of the Transformers Library
Explore the origins of HuggingFace and Transformers library, delving into transfer learning in NLP, open-source models, and the impact of community-driven AI research and development.
How to Add Machine Learning Capabilities With Just a Few Lines of Code
Discover how to integrate GitHub Copilot-like ML capabilities into products using the Hugging Face Inference API, demonstrated through building a VSCode extension for Python code comment generation.
The Future of Natural Language Processing
Explore transfer learning in NLP, covering model efficiency, generalization, fine-tuning, and inductive biases. Gain insights into current trends and future directions from HuggingFace's science lead.
Why Is Bing Unhinged? Let's Talk About Alignment and How to Fix It
Explores AI alignment challenges, focusing on Bing's issues, and discusses potential solutions like cognitive architecture and constitutional AI to ensure benevolent AI development.
Reinforcement Learning from Human Feedback - From Zero to ChatGPT
Explore Reinforcement Learning from Human Feedback, its foundations, and applications in advanced AI like ChatGPT. Gain insights into NLP, RL basics, and open questions in this emerging field.
Reinforcement Learning from Human Feedback - From Zero to ChatGPT
Explore Reinforcement Learning from Human Feedback, its role in ChatGPT, and key concepts in NLP and RL. Gain insights into RLHF's technical aspects and open research areas.
XLS-R: Large-Scale Cross-Lingual Speech Representation Learning on 128 Languages
Explore XLS-R, a groundbreaking cross-lingual speech model trained on 128 languages. Learn about its impressive performance in speech translation, recognition, and language identification tasks.
Hugging Face Workshops - Pretraining Language Models & CodeParrot
Explore pretraining language models and CodeParrot, a code-writing AI. Learn data transformation, batching, evaluation, and tackle coding challenges in this hands-on workshop.
Langchain Chains and Chaining Explained - GPT-3 LLM Tutorial with Streaming Responses, Multi Input
Learn to create Langchain chains using OpenAI GPT-3, including multi-input/output chains and streaming responses. Explore simple LLM chains, multi-LLM chains, and advanced techniques for efficient language model integration.
QA Chat with a Website - OpenAI Embeddings Tutorial: Use GPT-3 API and OpenAI ADA-2 Embeddings
Learn to create a QA chatbot using OpenAI embeddings and GPT-3 API. Convert website content for similarity search, set up the environment, and implement the system step-by-step.
Langchain ChatGPT Your Documents Challenge Part 2 with GPT-3 and OpenAI Embeddings and Streamlit UI
Build a ChatGPT-like chatbot using Langchain, GPT-3, and OpenAI embeddings. Includes Streamlit UI, file uploader, and Wikipedia API integration for answering questions based on uploaded documents and relevant context.
GPT-3 Superpowers with Langchain - How to Use Langchain Tutorial: Prompt Tools Explained
Explore LangChain's powerful prompt tools for GPT-3, including templates, input variables, and few-shot examples. Learn to enhance AI interactions and create custom workflows.