Run your own production inference code with Sagemaker
-
Updated
Jun 15, 2020 - Python
Run your own production inference code with Sagemaker
Basic MLPlatform includes Model Registry and Inference Server
A networked inference server for Whisper so you don't have to keep waiting for the audio model to reload for the x-hunderdth time.
Serve pytorch inference requests using batching with redis for faster performance.
An AI-powered mobile crop advisory app for farmers, gardeners that can provide information about crops using an image taken by the user. This supports 10 crops and 37 kinds of crop diseases. The AI model is a ResNet network that has been fine-tuned using crop images that were collected by web-scraping from Google Images and Plant-Village Dataset.
Effortlessly Deploy and Serve Large Language Models in the Cloud as an API Endpoint for Inference
Inference Server Implementation from Scratch for Machine Learning Models
Audio components for geniusrise framework
Vision and vision-multi-modal components for geniusrise framework
Roboflow's inference server to analyze video streams. This project extracts insights from video frames at defined intervals and generates informative visualizations and CSV outputs.
Text components powering LLMs & SLMs for geniusrise framework
Benchmark for machine learning model online serving (LLM, embedding, Stable-Diffusion, Whisper)
Session Based Real-time Hotel Recommendation Web Application
Friendli: the fastest serving engine for generative AI
Advanced inference pipeline using NVIDIA Triton Inference Server for CRAFT Text detection (Pytorch), included converter from Pytorch -> ONNX -> TensorRT, Inference pipelines (TensorRT, Triton server - multi-format). Supported model format for Triton inference: TensorRT engine, Torchscript, ONNX
Deploy DL/ ML inference pipelines with minimal extra code.
This is a repository for an object detection inference API using the Tensorflow framework.
The simplest way to serve AI/ML models in production
This is a repository for an nocode object detection inference API using the Yolov4 and Yolov3 Opencv.
Add a description, image, and links to the inference-server topic page so that developers can more easily learn about it.
To associate your repository with the inference-server topic, visit your repo's landing page and select "manage topics."