#大语言模型#Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.
#Awesome#Resources of our survey paper "Optimizing Edge AI: A Comprehensive Survey on Data, Model, and System Strategies"
CLIP as a service - Embed image and sentences, object recognition, visual reasoning, image classification and reverse image search
#Awesome#Resources of our survey paper "Optimizing Edge AI: A Comprehensive Survey on Data, Model, and System Strategies"
Large-scale Auto-Distributed Training/Inference Unified Framework | Memory-Compute-Control Decoupled Architecture | Multi-language SDK & Heterogeneous Hardware Support
#大语言模型#EmbeddedLLM: API server for Embedded Device Deployment. Currently support CUDA/OpenVINO/IpexLLM/DirectML/CPU
#计算机科学#Streamlining the process for seamless execution of PyCoral in running TensorFlow Lite models on an Edge TPU USB.
#大语言模型#Kdeps is an all-in-one AI framework for building Dockerized full-stack AI applications (FE and BE) that includes open-source LLM models out-of-the-box.
#自然语言处理#Генерация описаний к изображениям с помощью различных архитектур нейронных сетей
#计算机科学#Accelerating AI Training and Inference from Storage Perspective (Must-read Papers on Storage for AI)
Image Classifiers are used in the field of computer vision to identify the content of an image and it is used across a broad variety of industries, from advanced technologies like autonomous vehicles ...
The primary objective of this project was to build and deploy an image classification model for Scones Unlimited, a scone-delivery-focused logistic company, using AWS SageMaker.
#计算机科学#😊📸 Real-Time Facial Emotion Recognition using Deep Learning 🤖🧠
#自然语言处理#Successfully fine-tuned a pretrained DistilBERT transformer model that can classify social media text data into one of 4 cyberbullying labels i.e. ethnicity/race, gender/sexual, religion and not cyber...
#自然语言处理#Successfully developed a fine-tuned BERT transformer model which can accurately classify symptoms to their corresponding diseases upto an accuracy of 89%.
A cloud run function to invoke a prediction against a machine learning model that has been trained outside of a cloud provider.
#自然语言处理#Successfully developed a fine-tuned DistilBERT transformer model which can accurately predict the overall sentiment of a piece of financial news up to an accuracy of nearly 81.5%.
Example distributed system for ML model inference by using Kafka, including spring boot REST+JPA server with Java consumer program
#计算机科学#This project is a web-based application that uses a pre-trained Mask R-CNN model to detect and classify car damage types (scratch, dent, shatter, dislocation) from images. Users can upload an image of...