PulmoLens
hugging-face-workshop
| PulmoLens | hugging-face-workshop | |
|---|---|---|
| 3 | 1 | |
| 10 | 26 | |
| - | - | |
| 5.3 | 0.0 | |
| almost 1 year ago | about 2 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | Apache License 2.0 |
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PulmoLens
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I deployed a Deep-Learning model as a REST-API to detect Pneumonia using AWS tools
Link to proj: https://github.com/akkik04/PulmoLens
hugging-face-workshop
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NLP@AWS Newsletter 04/2022
Hugging Face on Amazon SageMaker and AWS Workshop Interested to use NLP to generate models in the style of your favourite poets? This workshop shows you how you can fine tune text generation models in the style of your favourite poets using Hugging Face on Amazon SageMaker.
What are some alternatives?
video-super-resolution-youtube
fraud-detection-using-machine-learning - Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker
amazon-sagemaker-examples - Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
aws-lambda-docker-serverless-inference - Serve scikit-learn, XGBoost, TensorFlow, and PyTorch models with AWS Lambda container images support.
SagemakerHuggingfaceDashboard - This is a solution that demonstrates how to train and deploy a pre-trained Huggingface model on AWS SageMaker and publish an AWS QuickSight Dashboard that visualizes the model performance over the validation dataset and Exploratory Data Analysis for the pre-processed training dataset.
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
sagemaker-feature-store-real-time-recommendations - Build a real-time recommendation engine for an e-commerce website leveraging SageMaker Feature Store as a core component of the solution.