Management Dashboard for Torchserve
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Updated
Jan 31, 2023 - Python
Management Dashboard for Torchserve
Serving PyTorch models with TorchServe 🔥
Deploy DL/ ML inference pipelines with minimal extra code.
Torchserve server using a YoloV5 model running on docker with GPU and static batch inference to perform production ready and real time inference.
Deploy FastAI Trained PyTorch Model in TorchServe and Host in Amazon SageMaker Inference Endpoint
A minimalistic and pluggable machine learning platform for Kubernetes.
TorchServe+Streamlit for easily serving your HuggingFace NER models
Deploy Swin Transformer using TorchServe
Pushing Text To Speech models into production using torchserve, kubernetes and react web app 😄
Slides and notebook for the workshop on serving bert models in production
FastAPI middleware for comparing different ML model serving approaches
Twin Neural Network Training with PyTorch and fast.ai and its Deployment with TorchServe on Amazon SageMaker
How to deploy TorchServe on an Amazon EKS cluster for inference.
Deploy FastAI Trained PyTorch Model in TorchServe and Host in GCP's AI-Platform Prediciton.
This paper compares Flask, FastAPI, and TorchServe for deploying PyTorch models. Flask is simple, FastAPI adds performance, and TorchServe is best for large-scale production. FastAPI is ideal for small deployments, while TorchServe suits complex environments. AWS Lambda is suggested for advanced use cases.
Quick and easy tutorial to serve HuggingFace sentiment analysis model using torchserve
DET is an end-to-end tool for extracting Key-Value pairs from a variety of documents, built entirely on PyTorch and served using TorchServe.
Predicting musical valence of Spotify songs using PyTorch.
This repo implements a minimalistic pytorch_lightning + neptune + torchserve flow for (computer vision) model training and deployment
TorchServe images with specific Python version working out-of-the-box.
Add a description, image, and links to the torchserve topic page so that developers can more easily learn about it.
To associate your repository with the torchserve topic, visit your repo's landing page and select "manage topics."