hugging-face-workshop VS PulmoLens

Compare hugging-face-workshop vs PulmoLens and see what are their differences.

hugging-face-workshop

A 90-minute hands on workshop about Hugging Face on SageMaker. (by aws-samples)

PulmoLens

aws-powered deep-learning pneumonia detection model deployed as a serverless rest-api 🤖🫁 (by akkik04)
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hugging-face-workshop PulmoLens
1 3
26 10
- -
0.0 5.3
about 2 years ago 12 months ago
Jupyter Notebook Jupyter Notebook
Apache License 2.0 Apache License 2.0
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hugging-face-workshop

Posts with mentions or reviews of hugging-face-workshop. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-04.
  • NLP@AWS Newsletter 04/2022
    2 projects | dev.to | 4 Apr 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.

PulmoLens

Posts with mentions or reviews of PulmoLens. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing hugging-face-workshop and PulmoLens you can also consider the following projects:

fraud-detection-using-machine-learning - Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker

video-super-resolution-youtube

aws-lambda-docker-serverless-inference - Serve scikit-learn, XGBoost, TensorFlow, and PyTorch models with AWS Lambda container images support.

amazon-sagemaker-examples - Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

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.

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.

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!