soumyac1999
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A high-throughput and memory-efficient inference and serving engine for LLMs
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.
A playbook for systematically maximizing the performance of deep learning models.
🦜🔗 Build context-aware reasoning applications
Hackable and optimized Transformers building blocks, supporting a composable construction.
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
An open-source remote desktop, and alternative to TeamViewer.
A python toolkit for parsing captions (in natural language) into scene graphs (as symbolic representations).
Python Implementation of 'Gibbs Sampling For The Uninitiated'.
Scripts to preprocess training and test data and to run fast_align and giza
🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support
Streamlit — A faster way to build and share data apps.
Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.
An argparse wrapper that doesn't make you say "argh" each time you deal with it.
This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages" published in Findings of the Association for Co…
TensorFlow parameterized model library
Search for scientific papers on the command line
Library for fast text representation and classification.
A library for efficient similarity search and clustering of dense vectors.
Quill is a modern WYSIWYG editor built for compatibility and extensibility
Parsers for scientific papers (PDF2JSON, TEX2JSON, JATS2JSON)
TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.