Articles for category: AI Tools

March 29, 2025

ikayaniaamirshahzad@gmail.com

🤗 PEFT welcomes new merging methods

Model merging has quickly become the de-facto standard of pushing the performance limits of large language models. On the Open LLM Leaderboard, we continue to notice merged models topping up the charts. Our very own Omar Sanseviero, made a little sprint on model merging and discovered interesting findings. The typical way of model merging, so far, has been to take a set of models and merge them. This post gives a nice primer on this topic. Generally, for merging multiple models, we first download their checkpoints and then perform merging. Depending on the merge algorithm and the sizes of the

March 29, 2025

ikayaniaamirshahzad@gmail.com

Cách Treo Tranh Mã Đáo Thành Công

Nếu bạn đang tìm kiếm cách treo tranh Mã Đáo sao cho vừa thể hiện được giá trị nghệ thuật của tác phẩm, vừa tạo nên không gian sống hài hòa và sang trọng, bài viết dưới đây sẽ cung cấp cho bạn những bí quyết cần thiết để “bắt tay” vào việc treo tranh một cách thành công. Tại Sao Tranh Mã Đáo Lại Đặc Biệt? Tranh Mã Đáo không chỉ đơn thuần là một tác phẩm nghệ thuật mà còn là biểu tượng của sự tinh tế, đậm chất truyền thống và sang trọng. Khi được bố trí

March 29, 2025

ikayaniaamirshahzad@gmail.com

Leading the Korean LLM Evaluation Ecosystem

In the fast-evolving landscape of Large Language Models (LLMs), building an “ecosystem” has never been more important. This trend is evident in several major developments like Hugging Face’s democratizing NLP and Upstage building a Generative AI ecosystem. Inspired by these industry milestones, in September of 2023, at Upstage we initiated the Open Ko-LLM Leaderboard. Our goal was to quickly develop and introduce an evaluation ecosystem for Korean LLM data, aligning with the global movement towards open and collaborative AI development. Our vision for the Open Ko-LLM Leaderboard is to cultivate a vibrant Korean LLM evaluation ecosystem, fostering transparency by enabling

March 29, 2025

ikayaniaamirshahzad@gmail.com

Top 10 Full Stack Development Companies in India 2025

India has emerged as a global hub for Full Stack Development, with numerous companies offering end-to-end web and mobile development solutions. These companies specialize in frontend and backend technologies, ensuring scalable, high-performance applications tailored to various business needs. With expertise in modern frameworks, cloud integration, and DevOps, these firms provide innovative and cost-effective development services to clients worldwide. Top 10 Full Stack Development Companies in India 2025 01. Aalpha Information Systems Aalpha Information Systems specializes in Full Stack Development services, delivering comprehensive web and mobile application solutions with expertise in both frontend and backend technologies. With a focus on scalability,

March 29, 2025

ikayaniaamirshahzad@gmail.com

When Women Make Headlines

Today, research has suggested that women are significantly less likely to make the news compared to men. In the most recent report published by the Global Media Monitoring Project (GMMP), the largest and longest running research on gender in the world’s news media, women were found to make up just 24% of news subjects and sources reported. According to this report, this number has not changed since 2010. In the context of news, headlines introduce, frame and contextualize a news story. Furthermore, research within the fields of educational and experimental psychology has demonstrated that news headlines can have a disproportionate

March 29, 2025

ikayaniaamirshahzad@gmail.com

Welcome Gemma – Google’s new open LLM

An update to the Gemma models was released two months after this post, see the latest versions in this collection. Gemma, a new family of state-of-the-art open LLMs, was released today by Google! It’s great to see Google reinforcing its commitment to open-source AI, and we’re excited to fully support the launch with comprehensive integration in Hugging Face. Gemma comes in two sizes: 7B parameters, for efficient deployment and development on consumer-size GPU and TPU and 2B versions for CPU and on-device applications. Both come in base and instruction-tuned variants. We’ve collaborated with Google to ensure the best integration into

March 29, 2025

ikayaniaamirshahzad@gmail.com

🚀 Why Kotlin is the Best Choice for Android Development in 2025!

If you’re still using Java for Android development, it’s time to ask: Why not Kotlin? 🤔 Since Google made Kotlin the official language for Android, it has skyrocketed in popularity. But what makes Kotlin the best choice for modern Android apps? Let’s break it down! 🔥 🚀 1. Less Code, More Productivity Kotlin is concise compared to Java. Fewer lines of code mean faster development, fewer bugs, and cleaner code. 🔹 Example: Defining a simple data class: Java: public class User { private String name; public User(String name) { this.name = name; } public String getName() { return name; }

March 29, 2025

ikayaniaamirshahzad@gmail.com

Introducing spaCy Tailored Pipelines · Explosion

Explosion is pleased to announce a new development services offering, spaCy Tailored Pipelines. We’ll build you a custom natural language processing pipeline, delivered in a standardized format using spaCy’s projects system. spaCy Tailored Pipelines is a consulting service, but we want it to feel like buying a tailored product. You’ll always get a price upfront, and you’ll get to try the solution before you buy it. Projects will be designed to be handed over to your development team, with as little custom code to maintain as possible. spaCy’s mission is “Industrial-strength NLP”, and spaCy Tailored Pipelines gets to the heart

March 29, 2025

ikayaniaamirshahzad@gmail.com

Introducing the Red-Teaming Resistance Leaderboard

Content warning: since this blog post is about a red-teaming leaderboard (testing elicitation of harmful behavior in LLMs), some users might find the content of the related datasets or examples unsettling. LLM research is moving fast. Indeed, some might say too fast. While researchers in the field continue to rapidly expand and improve LLM performance, there is growing concern over whether these models are capable of realizing increasingly more undesired and unsafe behaviors. In recent months, there has been no shortage of legislation and direct calls from industry labs calling for additional scrutiny on models – not as a means