amazon-sagemaker-local-mode VS quick-deploy

Compare amazon-sagemaker-local-mode vs quick-deploy and see what are their differences.

amazon-sagemaker-local-mode

Amazon SageMaker Local Mode Examples (by aws-samples)
sagemaker amazon-sagemaker Pytorch Catboost Lightgbm pycharm tensorflow-training pytorch-training sagemaker-processing prophet scikit-learn prophet-model hdbscan-clustering-algorithm huggingface huggingface-transformers Machine Learning delta-lake gensim-word2vec Dask Tensorflow
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quick-deploy

Optimize, convert and deploy machine learning models as fast inference API using Triton and ORT. Currently support Hugging Face transformers, PyToch, Tensorflow, SKLearn and XGBoost models. (by rodrigobaron)
huggingface-transformers Pytorch Tensorflow Sklearn Xgboost Onnx triton Machine Learning Deep Learning Inference Mlops
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pypi.org
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amazon-sagemaker-local-mode quick-deploy
1 1
232 6
1.3% -
7.7 0.0
about 1 month ago about 2 years ago
Python Python
MIT No Attribution Apache License 2.0
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amazon-sagemaker-local-mode

Posts with mentions or reviews of amazon-sagemaker-local-mode. We have used some of these posts to build our list of alternatives and similar projects.

quick-deploy

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

What are some alternatives?

When comparing amazon-sagemaker-local-mode and quick-deploy you can also consider the following projects:

mljar-supervised - Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

tritony - Tiny configuration for Triton Inference Server

mars - Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.

examples - 📝 Examples of how to use Neptune for different use cases and with various MLOps tools

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

kserve - Standardized Serverless ML Inference Platform on Kubernetes

nebuly - The user analytics platform for LLMs

pinferencia - Python + Inference - Model Deployment library in Python. Simplest model inference server ever.

amazon-sagemaker-local-mode vs mljar-supervised quick-deploy vs tritony amazon-sagemaker-local-mode vs mars quick-deploy vs examples amazon-sagemaker-local-mode vs aws-lambda-docker-serverless-inference quick-deploy vs kserve amazon-sagemaker-local-mode vs nebuly amazon-sagemaker-local-mode vs pinferencia