In this article, you will learn how to turn an open-weight language model into a decision model that classifies user intent, by fine-tuning Qwen3.5-4B on the CLINC150 dataset with Unsloth.
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In this article, you will learn how Python decorators work under the hood and how to build reliable ones for timing, retries, caching, and input validation.
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From November 5 to November 20, 2026 (starting at 8:00 a.m. UTC), 365 Data Science will grant free access to its entire learning platform. This limited-time opportunity allows aspiring AI professionals and data enthusiasts to enhance their skills and gain practical, hands-on experience, completely free of charge.
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In this article, you will learn what DiffusionGemma is, how its diffusion-based text generation differs from standard autoregressive language models, and how to run it with Hugging Face Transformers and vLLM.
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A model is a collection of numbers. The format used to store and compute with those numbers affects how much memory the model occupies, how quickly the hardware can move the numbers, and which arithmetic units can process them. Changing precision can therefore make inference faster without changing the model architecture.
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