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20NVIDIA Ingest is a set of microservices for parsing hundreds of thousands of complex, messy unstructured PDFs and other enterprise documents into metadata and text to embed into retrieval systems.
Python SDK for Milvus.
cuVS - a library for vector search and clustering on the GPU
Triton Backend for NVTabular
RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.
No description provided.
NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in production.
No description provided.
Merlin Models is a collection of deep learning recommender system model reference implementations
Core Utilities for NVIDIA Merlin
Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation, available for both PyTorch and Tensorflow.
A library that sits on top of RAPIDS cuDF library providing a range of benefits for processing extremely large tabular datasets, particularly those that don't fit in GPU or CPU memory. The highlights of NVTabular’s capabilities are fast terabyte-scale data preparation and accelerated tabular data loading, all on GPU, which streamline the first step for both training and inference to any deep recommender system pipelines.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
No description provided.
cuDF - GPU DataFrame Library
No description provided.
An implementation of a deep learning recommendation model (DLRM)
Kaggle Python docker image
No description provided.
No description provided.