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Run your own AI cluster at home with everyday devices 📱💻 🖥️⌚
`dattri` is a PyTorch library for developing, benchmarking, and deploying efficient data attribution algorithms.
A fast, effective data attribution method for neural networks in PyTorch
Implementation of Shadow Removal Algorithms
Persian/Farsi text to speech(TTS) training using coqui tts
DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models (ICLR 2024)
Toolkit to segment text into sentences or other semantic units in a robust, efficient and adaptable way.
Official implementation of ACL 2025 Findings paper "Autonomous Data Selection with Zero-shot Generative Classifiers for Mathematical Texts" (As Huggingface Daily Papers: https://huggingface.co/pape…
Repo for Rho-1: Token-level Data Selection & Selective Pretraining of LLMs.
Implementation of Estimating Training Data Influence by Tracing Gradient Descent (NeurIPS 2020)
pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation
OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)
💱 A curated list of data valuation (DV) to design your next data marketplace
Algorithms for explaining machine learning models
Influence Functions with (Eigenvalue-corrected) Kronecker-Factored Approximate Curvature
A robust, efficient, low-latency speech-to-text library with advanced voice activity detection, wake word activation and instant transcription.
very simple faster r-cnn implementation in pytorch1.x
chenyuntc/simple-faster-rcnn-pytorch 注释简化版
run this repository only depend python2.7 and Pytorch (0.3 or 0.4)
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
A collection of 1000+ survey papers on Natural Language Processing (NLP) and Machine Learning (ML).
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
Elegant Scraper and Crawler Framework for Golang