Vishengel

Vishengel's Stars

• facebookresearch/segment-anything

  The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

  Language:Jupyter Notebook47.4k3066665.6k

• openai/CLIP

  CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

  Language:Jupyter Notebook25.6k3234023.3k

• openai/openai-python

  The official Python library for the OpenAI API

  Language:Python22.8k3017943.2k

• tloen/alpaca-lora

  Instruct-tune LLaMA on consumer hardware

  Language:Jupyter Notebook18.6k1544692.2k

• datasciencescoop/Data-Science--Cheat-Sheet

  Cheat Sheets

  Language:TeX18.3k

• joonspk-research/generative_agents

  Generative Agents: Interactive Simulacra of Human Behavior

  17.3k1401262.2k

• hoffstadt/DearPyGui

  Dear PyGui: A fast and powerful Graphical User Interface Toolkit for Python with minimal dependencies

  Language:C++13.2k1571.4k686

• Sinaptik-AI/pandas-ai

  Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.

  Language:Python13.2k1097241.3k

• mlfoundations/open_clip

  An open source implementation of CLIP.

  Language:Python10.2k78484976

• doccano/doccano

  Open source annotation tool for machine learning practitioners.

  Language:Python9.5k1341.5k1.7k

• nebuly-ai/optimate

  A collection of libraries to optimise AI model performances

  Language:Python8.4k93201641

• eternnoir/pyTelegramBotAPI

  Python Telegram bot api.

  Language:Python8.1k2361.3k2k

• axolotl-ai-cloud/axolotl

  Go ahead and axolotl questions

  Language:Python7.8k48671863

• tyiannak/pyAudioAnalysis

  Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications

  Language:Python5.9k2103081.2k

• marqo-ai/marqo

  Unified embedding generation and search engine. Also available on cloud - cloud.marqo.ai

  Language:Python4.6k38242189

• huggingface/transfer-learning-conv-ai

  🦄 State-of-the-Art Conversational AI with Transfer Learning

  Language:Python1.7k85109432

• jrieke/traingenerator

  🧙 A web app to generate template code for machine learning

  Language:Python1.4k3710182

• Cadene/vqa.pytorch

  Visual Question Answering in Pytorch

  Language:Python7163348178

• mlfoundations/datacomp

  DataComp: In search of the next generation of multimodal datasets

  Language:Python650176455

• cccntu/minLoRA

  minLoRA: a minimal PyTorch library that allows you to apply LoRA to any PyTorch model.

  Language:Jupyter Notebook43210829

• GT-Vision-Lab/VQA

  Language:Python3622112139

• markdtw/vqa-winner-cvprw-2017

  Pytorch implementation of winner from VQA Chllange Workshop in CVPR'17

  Language:Python16411738

• projectmesa/mesa-examples

  User and showcase agent-based models developed using Mesa

  Language:Python1181248147

• wtfloris/hestia

  Hestia scrapes real estate websites for new rental listings

  Language:Python964436

• JVital2013/pihole-router

  How-to files for configuring a Pi-Hole as a Network Router

  572111

• ErikMinekus/traktor-scripts

  Python scripts for Traktor Pro

  Language:Python25407

• alanwang93/seq2seq-pytorch

  Seq2seq model with global attention implemented with PyTorch

  Language:Python18134

• rshivansh/San-Pytorch

  Let us try implementing SAN in pytorch from scratch

  Language:Python16206

• MokoSan/FSharpAdvent

  Language:HTML12417

• GrHound/imagemorph.c

  Program to apply random elastic rubbersheet transforms to Netpbm color (.ppm, i.e., P6 raw color) images for augmenting training sets in machine learning/deep learning. The program reads an input .ppm image from stdin and writes a ppm image to stdout. Original Author: Marius Bulacu (.pgm version for characters). Adapted for .ppm and color: Lambert Schomaker. Please cite: M Bulacu, A Brink, T van der Zant, L Schomaker (2009). Recognition of handwritten numerical fields in a large single-writer historical collection, 10th International Conference on Document Analysis and Recognition, pp. 808-812, DOI: 10.1109/ICDAR.2009.8

  Language:C6003