huggingpics
aws-lambda-docker-serverless-inference
huggingpics | aws-lambda-docker-serverless-inference | |
---|---|---|
1 | 1 | |
249 | 92 | |
- | - | |
0.0 | 4.0 | |
over 1 year ago | about 1 month ago | |
Jupyter Notebook | Jupyter Notebook | |
- | MIT No Attribution |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
huggingpics
aws-lambda-docker-serverless-inference
-
AWS - NLP newsletter - 2021. Aug.
GitHub: Train a BlazingText text classification algorithm in SageMaker, inference with AWS Lambda
What are some alternatives?
ganbert-pytorch - Enhancing the BERT training with Semi-supervised Generative Adversarial Networks in Pytorch/HuggingFace
amazon-sagemaker-examples - Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
multi-label-sentiment-classifier - How to build a multi-label sentiment classifiers with Tez and PyTorch
keytotext - Keywords to Sentences
jetson-containers - Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
python-machine-learning-book-3rd-edition - The "Python Machine Learning (3rd edition)" book code repository
hugging-face-workshop - A 90-minute hands on workshop about Hugging Face on SageMaker.
amazon-transcribe-output-word-document - An Amazon Transcribe demo to produce a Microsoft Word document containing the turn-by-turn transcription of the audio. This will include additional metadata depending upon the options selected, such as caller sentiment, category identification and issue detection
predict-subreddit - NLP model that predicts subreddit based on the title of a post
merloc-java - MerLoc is a live AWS Lambda function development and debugging tool. MerLoc allows you to run AWS Lambda functions on your local while they are still part of a flow in the AWS cloud remote.