RAG (Retrieval Augmented Generation) Framework for building modular, open source applications for production by TrueFoundry
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Updated
Feb 21, 2025 - Python
RAG (Retrieval Augmented Generation) Framework for building modular, open source applications for production by TrueFoundry
FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.
Boosting your Web Services of Deep Learning Applications.
Python + Inference - Model Deployment library in Python. Simplest model inference server ever.
Server for Physical AI Inference
A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model Deployment.
Starter app for fastai v3 model deployment on Render
A Beautiful Flask Web API for Yolov7 (and custom) models
Fast model deployment on any cloud 🚀
🤖 An automated machine learning framework for audio, text, image, video, or .CSV files (50+ featurizers and 15+ model trainers). Python 3.6 required.
Deploy DL/ ML inference pipelines with minimal extra code.
The official python package for NimbleBox. Exposes all APIs as CLIs and contains modules to make ML 🌸
Software Development Kit (SDK) for the Intel® Geti™ platform for Computer Vision AI model training.
gRPC server for hosting ML models trained on any framework in python
'Deploying machine learning models with a Flask API' tutorial, written for HyperionDev
Turn any OCR models into online inference API endpoint 🚀 🌖
Online Inference API for NLP Transformer models - summarization, text classification, sentiment analysis and more
Experiments with Model Training, Deployment & Monitoring
Client interface to Cleanlab Studio and the Trustworthy Language Model
mlserve turns your python models into RESTful API, serves web page with form generated to match your input data.
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