March 16, 2026 Python

Quiz: Speed Up Python With Concurrency

Interactive Quiz ⋅ 8 QuestionsBy Joseph Peart Share In this quiz, you’ll test your understanding of Speed Up Python With Concurrency. You’ll explore how I/O-bound programs face latency, which concurrency patterns to use, the differences between threading, asyncio, and multiprocessing, and how the Global Interpreter Lock (GIL) affects Python programs. The quiz contains 8 questions and there is no time limit. You’ll get 1 point for each correct answer. At the end of the quiz, you’ll receive a total score. […]

March 16, 2026 Python

Spyder: Your IDE for Data Science Development in Python

There are many different integrated development environments (IDEs) to choose from for Python development. One popular option for data-focused work is Spyder, an open-source Python IDE geared toward scientists, engineers, and data analysts. Its name comes from Scientific PYthon Development EnviRonment. Out of the box, it has powerful plotting, what-if, and profiling capabilities. It also integrates well with the data science ecosystem, is extensible with first- or third-party plugins, and has a relatively quick learning curve. How does Spyder stack […]

March 16, 2026 NLP

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March 15, 2026 huggingface

Beyond Semantic Similarity: Introducing NVIDIA NeMo Retriever’s Generalizable Agentic Retrieval Pipeline

We are thrilled to announce that NVIDIA NeMo Retriever team has developed a new agentic retrieval pipeline that has officially secured the #1 spot on the ViDoRe v3 pipeline leaderboard. In addition, this exact same pipeline architecture achieved the #2 spot on the highly demanding, reasoning-intensive BRIGHT leaderboard. In the rapidly evolving landscape of AI retrieval, many solutions are highly specialized, engineered to perform exceptionally well on specific, narrow tasks. However, real-world enterprise applications rarely have the luxury of perfectly […]

March 14, 2026 Python

Quiz: How to Use Ollama to Run Large Language Models Locally

Interactive Quiz ⋅ 6 QuestionsBy Joseph Peart Share In this quiz, you’ll test your understanding of How to Use Ollama to Run Large Language Models Locally. By working through this quiz, you’ll revisit how to install Ollama, pull and manage models, chat with local LLMs from your terminal, and connect them to AI coding tools. Running models locally means your prompts stay private and no API keys or cloud services are needed. See how well you remember the key commands […]

March 14, 2026 Python

Quiz: Splitting, Concatenating, and Joining Python Strings

Interactive Quiz ⋅ 10 QuestionsBy Martin Breuss Share How well do you know Python string manipulation? In this quiz, you’ll revisit concepts like string immutability, splitting and joining with different arguments, and building safe string operations for tasks like CSV handling. You’ll get hands-on practice with real examples from the Splitting, Concatenating, and Joining Strings in Python course. Ready to test your skills? The quiz contains 10 questions and there is no time limit. You’ll get 1 point for each […]

March 13, 2026 huggingface

Porting fairseq wmt19 translation system to transformers

March 13, 2026 huggingface

Leveraging Pre-trained Language Model Checkpoints for Encoder-Decoder Models

Transformer-based encoder-decoder models were proposed in Vaswani et al. (2017) and have recently experienced a surge of interest, e.g. Lewis et al. (2019), Raffel et al. (2019), Zhang et al. (2020), Zaheer et al. (2020), Yan et al. (2020). Similar

March 13, 2026 huggingface

How we sped up transformer inference 100x for 🤗 API customers

🤗 Transformers has become the default library for data scientists all around the world to explore state of the art NLP models and build new NLP features. With over 5,000 pre-trained and fine-tuned models available, in over 250 languages, it is a rich playground, easily accessible whichever framework you are working in. While experimenting with models in 🤗 Transformers is easy, deploying

March 13, 2026 huggingface

Fit More and Train Faster With ZeRO via DeepSpeed and FairScale

A guest blog post by Hugging Face fellow Stas Bekman As recent Machine Learning models have been growing much faster than the amount of GPU memory added to newly released cards, many users are unable to train or even just load some of those huge models onto their hardware. While there is an ongoing effort to distill some of those huge models

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