Python

Quiz: The LEGB Rule & Understanding Python Scope

Interactive Quiz ⋅ 8 QuestionsBy Joseph Peart Share In this quiz, you’ll test your understanding of The LEGB Rule & Understanding Python Scope. By working through this quiz, you’ll revisit how Python resolves names using the LEGB rule, what the local, enclosing, global, and built-in scopes look like in practice, and how the global and nonlocal statements let you reach across scope boundaries. The quiz contains 8 questions and there is no time limit. You’ll get 1 point for each […]

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Python

Quiz: Building Type-Safe LLM Agents With Pydantic AI

Interactive Quiz ⋅ 9 QuestionsBy Joseph Peart Share In this quiz, you’ll test your understanding of Building Type-Safe LLM Agents With Pydantic AI. By working through this quiz, you’ll revisit how Pydantic AI returns structured outputs from LLMs, how validation retries improve reliability, how tools and function calling work, how dependency injection flows through RunContext, and what trade-offs to expect when running agents in production. The quiz contains 9 questions and there is no time limit. You’ll get 1 point […]

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Python

Building Type-Safe LLM Agents With Pydantic AI

Pydantic AI is a Python framework for building LLM agents that return validated, structured outputs using Pydantic models. Instead of parsing raw strings from LLMs, you get type-safe objects with automatic validation. If you’ve used FastAPI or Pydantic before, then you’ll recognize the familiar pattern of defining schemas with type hints and letting the framework handle the type validation for you. By the end of this video course, you’ll understand that: Pydantic AI uses BaseModel classes to define structured outputs […]

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huggingface

Adding Benchmaxxer Repellant to the Open ASR Leaderboard

“When a measure becomes a target, it ceases to be a good measure.” (Goodhart’s Law) TLDR: Appen Inc. and DataoceanAI have provided high-quality English ASR datasets covering scripted and conversational speech over multiple accents. To prevent potential risks of benchmaxxing or test-set contamination, we will keep these datasets private for a high-quality measure of performance on multiple tasks. We’re not updating the average WER at this time: by default, the leaderboard’s Average WER remains computed on public datasets only. You […]

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huggingface

vLLM V0 to V1: Correctness Before Corrections in RL

PipelineRL uses vLLM as the inference engine for rollout generation. The inference engine samples tokens and returns token logprobs; the trainer uses those logprobs to compute policy ratios, KL, clip rate, entropy, and reward. Any discrepancy in how those logprobs are computed can change the training dynamics. This is the train-inference mismatch we needed to eliminate during the vLLM V0 to V1 migration. TL;DR. vLLM V1 matched our vLLM V0 reference after we fixed four things: processed rollout logprobs, V1-specific […]

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huggingface

EMO: Pretraining mixture of experts for emergent modularity

🧠 Models: https://huggingface.co/collections/allenai/emo | 📄 Tech report: https://allenai.org/papers/emo | 💻 Code: https://github.com/allenai/EMO | 📊 Visualization: https://emovisualization.netlify.app/ Today we’re releasing EMO, a new mixture-of-experts (MoE) model pretrained end-to-end so that modular structure emerges directly from the data without relying on human-defined priors. EMO lets you use a small subset of its experts – just 12.5% of the total – for a given task while keeping near full-model performance, and still works as a strong general-purpose model when all experts are used […]

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huggingface

MachinaCheck: Building a Multi-Agent CNC Manufacturability System on AMD MI300X

Built at the AMD Developer Hackathon on lablab.ai — May 2026 The Problem We Solved Walk into any small CNC machine shop and ask the manager how they decide whether to accept a customer job. The answer is almost always the same: they print the drawing, read every dimension by hand, walk around the shop checking which tools are available, estimate whether their machines can hold the required tolerances, and write notes on a clipboard. The whole process takes 30 […]

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Python

Quiz: Memory Management in Python

Interactive Quiz ⋅ 10 QuestionsBy Joseph Peart Share In this quiz, you’ll test your understanding of Memory Management in Python. By working through this quiz, you’ll revisit how Python handles memory allocation and freeing, the role of the Global Interpreter Lock, and how CPython organizes memory using arenas, pools, and blocks. Give it a shot! The quiz contains 10 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

Quiz: Qt Designer and Python: Build Your GUI Applications Faster

Interactive Quiz ⋅ 10 QuestionsBy Joseph Peart Share In this quiz, you’ll test your knowledge of Qt Designer and Python: Build Your GUI Applications Faster. By working through this quiz, you’ll revisit how Qt Designer turns visual designs into .ui files, how layout managers control widget geometry, how signals and slots connect user actions to your code, and how to load .ui files into a PyQt application with pyuic5 or uic.loadUi(). The quiz contains 10 questions and there is no […]

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