Articles for category: AI Tools

Episode #300 – Building a data science startup (panel)

You’ve heard that software developers and startups go hand-in-hand. But what about data scientists? Of course they! But how do you turn your data science skill set into a data science On this episode, I welcome back 4 prior guests who have all walked their own version of this path and are currently running successful Python-based Data Science startups. Collapse transcript 00:00 You’ve heard that software developers and startups go hand in hand, but what about data scientists? 00:04 Of course they do. But how do you turn your data science skill set into a data science 00:09 business

SDXL in 4 steps with Latent Consistency LoRAs

Latent Consistency Models (LCM) are a way to decrease the number of steps required to generate an image with Stable Diffusion (or SDXL) by distilling the original model into another version that requires fewer steps (4 to 8 instead of the original 25 to 50). Distillation is a type of training procedure that attempts to replicate the outputs from a source model using a new one. The distilled model may be designed to be smaller (that’s the case of DistilBERT or the recently-released Distil-Whisper) or, in this case, require fewer steps to run. It’s usually a lengthy and costly process

AS diferenças entre type e interface no TypeScript

O que é type ? No TypeScript, as interfaces são usadas para definir a forma de objetos, enquanto os types são usados para definir tipos de dados mais complexos. Uma das maiores diferenças entre tipos e interfaces é que interfaces são abertas e tipos são fechados. Isso signifca que você pode extender interfaces declarando uma segunda vez. // Por outro lado tipos não podem ser alterados fora da própria declaração. Diferenças Interface Type Uso Definir a forma de objetos ou a assinatura de funções Definir tipos de dados mais complexos Expressão Sempre uma declaração de forma Pode ser uma declaração

Thinc · A refreshing functional take on deep learning

🔮 Use any framework Switch between PyTorch, TensorFlow and MXNet models without changing your application, or even create mutant hybrids using zero-copy array interchange. 🚀 Type checking Develop faster and catch bugs sooner with sophisticated type checking. Trying to pass a 1-dimensional array into a model that expects two dimensions? That’s a type error. Your editor can pick it up as the code leaves your fingers. 🐍 Awesome config Configuration is a major pain for ML. Thinc lets you describe trees of objects with references to your own functions, so you can stop passing around blobs of settings. It’s simple,

Open LLM Leaderboard: DROP deep dive

Recently, three new benchmarks were added to the Open LLM Leaderboard: Winogrande, GSM8k and DROP, using the original implementations reproduced in the EleutherAI Harness. A cursory look at the scores for DROP revealed something strange was going on, with the overwhelming majority of models scoring less than 10 out of 100 on their f1-score! We did a deep dive to understand what was going on, come with us to see what we found out! Initial observations DROP (Discrete Reasoning Over Paragraphs) is an evaluation where models must extract relevant information from English-text paragraphs before executing discrete reasoning steps on them

🔐 Linux, Locked and Loaded: A DevOps Primer Before I Git Going

👋 Hello Peeps!Well, what do you know—I finished the Linux course way earlier than expected!My goal was to wrap it up before the end of next week, but thanks to a happy little network outage at work (shoutout to IT—you’re doing your best, legends 💻🔥), I had some unexpected downtime and decided to power through. 🧠 Real TalkTo be honest, I skipped a few overly deep sections—because hey, I’m not trying to become a full-blown sysadmin.My focus is learning just enough Linux to troubleshoot like a boss, understand what’s going on under the hood, and be self-sufficient in a DevOps

Large Language Models Out-of-the-Box Acceleration with AMD GPU

Earlier this year, AMD and Hugging Face announced a partnership to accelerate AI models during the AMD’s AI Day event. We have been hard at work to bring this vision to reality, and make it easy for the Hugging Face community to run the latest AI models on AMD hardware with the best possible performance. AMD is powering some of the most powerful supercomputers in the World, including the fastest European one, LUMI, which operates over 10,000 MI250X AMD GPUs. At this event, AMD revealed their latest generation of server GPUs, the AMD Instinct™ MI300 series accelerators, which will soon

Windows Subsystem for Linux (WSL)

Introduction In my early days of learning DevOps, one of the biggest challenges I faced was setting up a Linux environment on my laptop. Since I was already comfortable with Windows, I found it difficult to make a complete switch to Linux, mainly because I still needed access to certain Windows applications. I initially tried dual-booting, but it felt cumbersome—I wanted both operating systems to work side by side without rebooting. Then I experimented with virtual machines (VMs), which worked but drained my laptop’s battery too quickly. During my search for a better solution, I discovered Windows Subsystem for Linux

Rewrite for spaCy v3, Transformer component and TransformerListener, plus more functions · explosion/spacy-transformers · GitHub

Releases v1.0.0 ines released this 01 Feb 10:10 This release requires spaCy v3. ✨ New features and improvements Rewrite library from scratch for spaCy v3.0. Transformer component for easy pipeline integration. TransformerListener to share transformer weights between components. Built-in registered functions that are available in spaCy if spacy-transformers is installed in the same environment. 📖 Documentation You can’t perform that action at this time. Source link