Python

Quiz: Structuring Your Python Script

Interactive Quiz ⋅ 8 QuestionsBy Joseph Peart Share In this quiz, you’ll test your understanding of the video course Structuring Your Python Script. By working through this quiz, you’ll revisit how to make a Python script executable with a shebang, organize your imports per PEP 8, automatically sort imports with ruff, and define a clear entry point using if __name__ == “__main__”. These habits help you transition from quick experiments in the REPL to writing Python scripts that are easy […]

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Python

Quiz: Python’s Format Mini-Language for Tidy Strings

Interactive Quiz ⋅ 12 QuestionsBy Joseph Peart Share In this quiz, you’ll test your understanding of Python’s Format Mini-Language for Tidy Strings. By working through this quiz, you’ll revisit how format specifiers work inside f-strings and str.format(), including alignment and width fields, decimal precision, type representations, thousand separators, sign handling, dynamic specifiers, and percentage formatting. The quiz contains 12 questions and there is no time limit. You’ll get 1 point for each correct answer. At the end of the quiz, […]

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Python

Structuring Your Python Script

You may have begun your Python journey interactively, exploring ideas within Jupyter Notebooks or through the Python REPL. While that’s great for quick experimentation and immediate feedback, you’ll likely find yourself saving code into .py files. However, as your codebase grows, knowing where things should go in your script becomes increasingly important. Transitioning from interactive environments to structured scripts helps promote readability, enabling better collaboration and more robust development practices. This video course shows you the foundations of organizing a […]

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Python

Quiz: Regular Expressions: Regexes in Python (Part 1)

Interactive Quiz ⋅ 10 QuestionsBy Joseph Peart Share In this quiz, you’ll test your understanding of Regular Expressions: Regexes in Python (Part 1). By working through this quiz, you’ll revisit how to use the re module to search for patterns, build character classes and anchors, group and capture substrings, and apply flags like re.IGNORECASE to control matching behavior. The quiz contains 10 questions and there is no time limit. You’ll get 1 point for each correct answer. At the end […]

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Python

Python sleep(): How to Add Time Delays to Your Code

Sometimes you need to make Python sleep, wait, or pause before running the next line of code. Whether you’re spacing out API requests, pacing a thread, or adding a delay to terminal output, Python’s time.sleep() function is the standard tool: from time import sleep sleep(3) # Pause execution for 3 seconds Beyond time.sleep(), Python provides different ways to add time delays depending on the context, including threads, async code, and GUI applications. By the end of this tutorial,    

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huggingface

Harness, Scaffold, and the AI Agent Terms Worth Getting Right

When a field evolves quickly, its vocabulary often evolves faster than its shared understanding. Terms start to blur, get reused in different contexts, or become shorthand for ideas that are never fully explained. We are currently seeing this happen in the field of AI Agents, where concepts are getting mixed together, some are renamed, and others are widely used for a few months before quietly disappearing. This can be overwhelming for newcomers, and even for practitioners trying to keep up […]

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huggingface

Shipping a Trillion Parameters With a Hub Bucket: Delta Weight Sync in TRL

TL;DR, because you have models to train and we respect that: Async RL has a dirty secret: every step, the trainer has to ship the whole model to the inference engine. For a 7B in bf16 that is 14 GB. For a frontier 1T model checkpoint that is on the order of a terabyte. Per step. It turns out you do not have to. Between two consecutive RL optimizer steps, roughly 99% of bf16 weights are bit-identical (and never less […]

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huggingface

Reachy Mini goes fully local

After building your Reachy Mini, you’ll install the conversation app and start talking to it. Until now, you had to send your audio to a server. But not anymore. Today we’ll walk you through running the whole stack locally. This stack is powered by speech-to-speech, our cascaded VAD → STT → LLM → TTS pipeline that exposes a Realtime API-compatible /v1/realtime WebSocket. Once you launch the backend, point the robot at it from the UI. Cascades are the most flexible […]

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huggingface

ITBench-AA: Frontier Models Score Below 50% on the First Benchmark for Agentic Enterprise IT Tasks — by Artificial Analysis and IBM

Artificial Analysis and IBM Software Innovation Lab are launching ITBench-AA, the first in a new series of benchmarks evaluating models on agentic enterprise IT tasks, starting with Site Reliability Engineering tasks where frontier models score below 50% ITBench-AA’s SRE tasks benchmark model performance on Kubernetes incident response, where models and agents must diagnose live systems by reading logs, tracing dependencies, and identifying root-cause entities across complex infrastructure. The underlying ITBench dataset has been developed by IBM, leveraging deep expertise in […]

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huggingface

Profiling in PyTorch (Part 1): A Beginner’s Guide to torch.profiler

What you cannot profile, you cannot optimize. Whether you are trying to squeeze more tokens per second out of a Large Language Model (LLM), shave milliseconds off inference, or just understand why your training loop runs slower than the spec sheet promises, the path eventually runs through profiling. The catch is that profiling has a steep on-ramp. The traces are dense walls of colored rectangles. The events carry intimidating names. Most tutorials assume you can already read them. So even […]

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