regstuff's starred repositories
llm-course
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
gpt-crawler
Crawl a site to generate knowledge files to create your own custom GPT from a URL
ChatGPT-AutoExpert
🚀🧠💬 Supercharged Custom Instructions for ChatGPT (non-coding) and ChatGPT Advanced Data Analysis (coding).
alignment-handbook
Robust recipes to align language models with human and AI preferences
PySceneDetect
:movie_camera: Python and OpenCV-based scene cut/transition detection program & library.
deepsparse
Sparsity-aware deep learning inference runtime for CPUs
image-match
🎇 Quickly search over billions of images
AICoverGen
A WebUI to create song covers with any RVC v2 trained AI voice from YouTube videos or audio files.
chromaprint
C library for generating audio fingerprints used by AcoustID
whisper-ctranslate2
Whisper command line client compatible with original OpenAI client based on CTranslate2.
inaSpeechSegmenter
CNN-based audio segmentation toolkit. Allows to detect speech, music, noise and speaker gender. Has been designed for large scale gender equality studies based on speech time per gender.
llama-2-resources
Useful tools and links for Llama 2.
Large_dataset_translator
Translate large dataset to any language with google translation api and multithread processing, no key required !
blitz-embed
C++ inference wrappers for running blazing fast embedding services on your favourite serverless like AWS Lambda. By Prithivi Da, PRs welcome.
perspectives
Pandas-based library for emotion graphing and semantic search with LMs
E-Commerce
This is a Flipkart clone eCommerce project developed using the MERN (MongoDB, Express.js, React.js, Node.js) stack.
aztraphile
mature Python Azure Function App in 8 lines of config <⚡>
Temporal-segmentation-Shot-boundary
A novel method for SBD using LBP-HF and Canny edge defference
BERTSimilar
Get Similar Words and Embeddings using BERT Models
Audio-Matching-Shazam-Style-Using-Hashing
I have taken the premade algorithm from the offical shazam research paper and try to implement it on our local dataset.