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Caption images across your datasets with state of the art models from Hugging Face and Replicate!

Unofficial Hugging Face client with a dash of personality

An HF's Smolagent to automate molecular dynamics simulations using GROMACS.

Convert images into captivating audio stories using image-to-text, language models, and text-to-speech technologies. Upload images, generate stories, and listen to the narrated audio clips. A fun project combining AI and creativity.

Simple repo to finetune an LLM hosted on Hugging Face by creating a LORA

Run IBM Granite 4.0 locally on Raspberry Pi 5 with Ollama.This is a privacy-first AI. Your data never leaves your device because it runs 100% locally. There are no cloud uploads and no third-party tracking.

Taxonomy Completion with Embedding Quantization and an LLM-based Pipeline: A Case Study in Computational Linguistics

template for duplicating and executing Hugging Face Spaces either on SM Studio Lab, Google Colab, or locally.

AI-powered emotion detection & personalized recommendations using NLP and machine learning

Code and dataset for paper - Application of Deep Learning in Generating Structured Radiology Reports: A Transformer-Based Technique

Workshop for making a Telegram bot and using APIs.

The project,being part of Kagglex BIPOC Mentorship Program final project, aims to train two separate Hindi ASR models using the Facebook Wav2Vec2 (300M parameters) and OpenAI Whisper-Small models, respectively. The goal is to compare their performance, with a target WER of less than 13%, across various Hindi accents and dialects.

Use Transformers.js from Blazor WebAssembly to run pretrained models with the ONNX Runtime in the browser.

Gradio-based web UI for medical image interpretation using Google's MedGemma vision-language model.

Wrapper for stable version of RoBERTa language models

Easy to use command line assistant using OpenAssistant's model API

Learn LangChain for Genearative AI with OpenAI API using Python

One API to access Large Language Models in Java

Library for Federated Emergence & Foundation Models

Using Semantic Kernel to obtain answer from a PDF document, with embeddings stored in Redis and HuggingFace to create embeddings.