Up to 3.2x Faster Inference with LFM2.5-DSpark
The introduction of LFM2.5-DSpark enhances inference speed by up to 3.2 times, benefiting developers in AI.
#transformers
10 articles tagged with “transformers”.
These startups are chasing the next big thing in LLMs
An MIT Technology Review feature in its What's Next series explores startups seeking the next breakthrough in large language models.
Introducing Cosmos 3 Edge
Hugging Face has launched Cosmos 3 Edge, a new tool aimed at developers to enhance AI model development and deployment on edge devices.
Model Routing Is Simple. Until It Isn’t.
The Hugging Face Blog discusses the intricacies of model routing, highlighting challenges that arise in AI systems and their impact on performance.
How Speech-to-Text Works: From Sound Waves to Transcripts
Speech recognition went from a brittle research problem to a solved-ish commodity in about three years. Here is the pipeline that made it work — and where it still breaks.
How Transformers Work: The Architecture Behind Every Modern AI
Almost every AI you use — ChatGPT, Claude, Gemini — is a transformer. Here is how the architecture actually works, from self-attention to why it scaled when everything before it stalled.
Profiling in PyTorch (Part 3): Attention is all you profile
The article delves into various profiling methods in PyTorch, emphasizing attention mechanisms in models to optimize performance.
Hugging Face Transformers: The Open-Source Standard for Working With AI Models
Transformers is the open-source Python library that made state-of-the-art AI models accessible to everyone. Here is what it does, who should use it, and where it fits in a modern AI stack.
BERT: The Paper That Taught Machines to Read Both Directions
Before GPT dominated headlines, BERT showed that pretraining a Transformer to read text in both directions could transform language understanding. Here is what the landmark 2018 paper introduced.
Attention Is All You Need: The Paper Behind Every Modern AI Model
Every modern language model — GPT, Claude, Gemini, Llama — descends from one 2017 paper. Here is what 'Attention Is All You Need' actually proposed, in plain English, and why it changed everything.