This video series explores explore the environmental impact of artificial intelligence and challenge the narrative that AI is inherently sustainable. I break down the real…
How to Measure the Carbon Footprint of Your Local Mistral-Poet LLM Running on Ollama with CodeCarbon
This video series explores explore the environmental impact of artificial intelligence and challenge the narrative that AI is inherently sustainable. I break down the real…
This video series explores explore the environmental impact of artificial intelligence and challenge the narrative that AI is inherently sustainable. I break down the real…
Continue reading → Measuring AI’s Carbon Footprint and Impact with CodeCarbon & Eco2AI
This video series explores the creation of an AI-powered image search application using Streamlit, open_clip, and faiss. The application enables users to search for images…
This video covers advanced techniques for analyzing subtitle files using machine learning models. We explore a Streamlit application that uses the spaCy library to load…
This video series covers advanced techniques for image captioning and face recognition using machine learning models. We explore the BLIP model for generating image captions,…
In this video, the underlying user story for this code is straightforward: to establish a semantic match between all existing keywords in a CMS (such…
Continue reading → Using Semantic Similarity with a CMS #ia #nlp #cms #api #python
An article exploring the process for testing the output of Large Language Models (LLMs) using a tool called “promptfoo.” This tool allows developers to evaluate…
Continue reading → Promptfoo: The Ultimate Tool for Ensuring LLM Quality and Reliability (Part 2)
An article exploring the process for testing the output of Large Language Models (LLMs) using a tool called “promptfoo.” This tool allows developers to evaluate…
Continue reading → Promptfoo: The Ultimate Tool for Ensuring LLM Quality and Reliability (Part 1)
This video is part of a post “Building a Vue.js SPA (Single Page Application) Frontend with FastAPI Backend for AI Integration” QUICK DESCRIPTION Transitioning from…
Continue reading → Video #1 Scaffold Your First Vitejs App: Comprehensive Beginner’s Guide
This video is part of a post “Empower Your Workflow: Harnessing the Power of LM Studio and Ollama for Seamless Local LLM Execution” POST: https://wp.me/p3Vuhl-3iX…
This video is part of a post “Empower Your Workflow: Harnessing the Power of LM Studio and Ollama for Seamless Local LLM Execution” POST: https://wp.me/p3Vuhl-3iX…
This video is part of a post “Crafting Fluent Translation API: A quick Journey into Text Translation with NLLB, HuggingFace, and FastAPI, Plus a small…
This video is part of a post “Crafting Fluent Translation API: A quick Journey into Text Translation with NLLB, HuggingFace, and FastAPI, Plus a small…
This video is part of a post “Unlocking Speech-to-Text: Harnessing the Power of the OpenAI Whisper API with FastAPI Integration.” This file “009_openai_whisper_fastapi.py” is POC…
Continue reading → Using #whisper & #fastapi : Creating a #multilingual Audio #api with #whisper
POC from “005_fastapi_tiangolo_tutorial_sql_databases”: The example given by the official documentation of FastAPI with SQLAlchemy. POC “007_sql_databases_peewee”: The example given by the official documentation of FastAPI…
POC from 008_fastapi_mysql_restapi: Using Docker to create a MYSQL database and a PhpMyAdmin instance connected to FastAPI POC. This video is part of the post…
I already mention this POC. The files are a mix between logical code written by ChatGPT (I have given the prompt in the main.py) and…
A quite simple, educational and hybrid project that demonstrate how-to create an API with FastAPI (backend) that will be the backend a web app made…
Continue reading → #2 How-to create an API with FastAPI, backend for a web app made with Streamlit
I only grab the API and the test (pytest) from this project. In reality, it is a bit more extended project, made by Microsoft’s people…
Continue reading → #3 How-to create an API with FastAPI and start testing it with pytest