The Must-Know Topics for an LLM Engineer
From tokenisation to evaluation : how modern language models actually work in practice The post The Must-Know Topics for an LLM Engineer appeared first on Towards Data Science.
Machine Learning Mastery Blog·
Language models (LMs), at their core, are text-in and text-out systems.
Read full articleFrom tokenisation to evaluation : how modern language models actually work in practice The post The Must-Know Topics for an LLM Engineer appeared first on Towards Data Science.
These ares seven unconventional uses of LLMs that go far beyond usual chat interface and conversations.
The following article originally appeared on the Asimov’s Addendum Substack and is being republished here with the author’s permission. Are LLMs reliable? LLMs have built up a reputation for being unreliable. Small changes in the input can lead to massive changes in the output. The same prompt run twice can give different or contradictory answers. […]
Merge LLMs easily with Unsloth Studio's no-code GUI and combine models without retraining.
Imagine asking your AI model, “What’s the weather in Tokyo right now?” and instead of hallucinating an answer, it calls your actual Python function, fetches live data, and responds correctly. That’s how empowering the tool call functions in the Gemma 4 from Google are. A truly exciting addition to open-weight AI: this function calling is […] The post Gemma 4 Tool Calling Explained: Build AI Agents with Function Calling (Step-by-Step Guide) appeared first on Analytics Vidhya.