Articles for category: AI Tools

March 29, 2025

ikayaniaamirshahzad@gmail.com

Deploy Embedding Models with Hugging Face Inference Endpoints

The rise of Generative AI and LLMs like ChatGPT has increased the interest and importance of embedding models for a variety of tasks especially for retrievel augemented generation, like search or chat with your data. Embeddings are helpful since they represent sentences, images, words, etc. as numeric vector representations, which allows us to map semantically related items and retrieve helpful information. This helps us to provide relevant context for our prompt to improve the quality and specificity of generation. Compared to LLMs are Embedding Models smaller in size and faster for inference. That is very important since you need to

March 29, 2025

ikayaniaamirshahzad@gmail.com

#122 Ines Montani’s DevJourney Podcast Interview

Transcript ⚠ The following transcript was automatically generated. ❤ Help us out, Submit a pull-request to correct potential mistakes Ines Montani 0:00He was like, hey, how would you feel about building a visualizer for syntax. So if you have like a sentence, different words have different types. Something is a verb, something is a noun, and then they connected to each other something is the subject something. So the object and a different levels of complexity of this and the computer can nowadays quite reliably predict these types of things. And even back then could train a system to do

March 29, 2025

ikayaniaamirshahzad@gmail.com

The N Implementation Details of RLHF with PPO

RLHF / ChatGPT has been a popular research topic these days. In our quest to research more on RLHF, this blog post attempts to do a reproduction of OpenAI’s 2019 original RLHF codebase at openai/lm-human-preferences. Despite its “tensorflow-1.x-ness,” OpenAI’s original codebase is very well-evaluated and benchmarked, making it a good place to study RLHF implementation engineering details. We aim to: reproduce OAI’s results in stylistic tasks and match the learning curves of openai/lm-human-preferences. present a checklist of implementation details, similar to the spirit of The 37 Implementation Details of Proximal Policy Optimization; Debugging RL, Without the Agonizing Pain. provide a

March 29, 2025

ikayaniaamirshahzad@gmail.com

Mejores prácticas para Amazon Inspector

La gestión de vulnerabilidades es un pilar fundamental en la seguridad de redes, aplicaciones e infraestructuras. Su objetivo es minimizar la exposición a riesgos y proteger los datos sensibles de una organización. Dentro de AWS, Amazon Inspector juega un papel clave en este proceso, proporcionando escaneo continuo de vulnerabilidades en workloads. En este post, exploraremos las mejores prácticas para aprovechar Amazon Inspector de manera efectiva. Veremos cómo gestionar hallazgos a gran escala, optimizar la administración en entornos multi-cuenta y aplicar estrategias de priorización para enfocarse en las amenazas más críticas. Amazon Inspector es un servicio de gestión de vulnerabilidades que

March 29, 2025

ikayaniaamirshahzad@gmail.com

Microsoft Azure Web App – Error 404

You may be seeing this error due to one of the reasons listed below : Custom domain has not been configured inside Azure. See how to map an existing domain to resolve this. Client cache is still pointing the domain to old IP address. Clear the cache by running the command ipconfig/flushdns. Checkout App Service Domain FAQ for more questions. Source link

March 29, 2025

ikayaniaamirshahzad@gmail.com

Interactively explore your Huggingface dataset with one line of code

The Hugging Face datasets library not only provides access to more than 70k publicly available datasets, but also offers very convenient data preparation pipelines for custom datasets. Renumics Spotlight allows you to create interactive visualizations to identify critical clusters in your data. Because Spotlight understands the data semantics within Hugging Face datasets, you can get started with just one line of code: import datasets from renumics import spotlight ds = datasets.load_dataset('speech_commands', 'v0.01', split='validation') spotlight.show(ds) Spotlight allows to leverage model results such as predictions and embeddings to gain a deeper understanding in data segments and model failure modes: ds_results = datasets.load_dataset('renumics/speech_commands-ast-finetuned-results',

March 29, 2025

ikayaniaamirshahzad@gmail.com

Mastering Marketing Automation with LouiseBot: The AppSumo Revelation

Master your Marketing Strategy with LouiseBot: An AppSumo Game-changer Introduction In the contemporary digital sphere, marketing automation tools have revolutionized the way brands engage with their audience. Tech-savvy marketers are always on the lookout for tools that can streamline their processes, optimize their strategies, and drive actionable results. One such groundbreaking tool on the market is LouiseBot, available at AppSumo ( This article will delve into what makes LouiseBot a must-have in your marketing arsenal. What is LouiseBot? LouiseBot is an innovative marketing automation tool designed to help businesses automate their social media presence, email marketing, and content creation. It’s

March 29, 2025

ikayaniaamirshahzad@gmail.com

Python Software Foundation Fellow Members for Q3 2020

It’s that time of year! Let us welcome the new PSF Fellows for Q3! The following people continue to do amazing things for the Python community: Débora Azevedo Twitter, Website Ines Montani Twitter, GitHub, Website John Roa Karolina Ladino Website, Twitter Katia Lira Twitter Mariatta Wijaya Twitter, GitHub Sponsor, GitHub, LinkedIn Melissa Weber Mendonça GitHub, Twitter Ng Swee Meng LinkedIn, GitHub, Twitter, Instagram Nilo Ney Coutinho Menezes GitHub, Blog, Twitter, Website Park Hyun-woo GitHub, Twitter Ram Rachum GitHub, Blog Sebastian Vetter LinkedIn, Website Thank you for your continued contributions. We have added you to our Fellow roster online. The above members

March 29, 2025

ikayaniaamirshahzad@gmail.com

Train Your Own Coding Assistant

In the ever-evolving landscape of programming and software development, the quest for efficiency and productivity has led to remarkable innovations. One such innovation is the emergence of code generation models such as Codex, StarCoder and Code Llama. These models have demonstrated remarkable capabilities in generating human-like code snippets, thereby showing immense potential as coding assistants. However, while these pre-trained models can perform impressively across a range of tasks, there’s an exciting possibility lying just beyond the horizon: the ability to tailor a code generation model to your specific needs. Think of personalized coding assistants which could be leveraged at an