aws-lambda-docker-serverless-inference VS multi-label-sentiment-classifier

Compare aws-lambda-docker-serverless-inference vs multi-label-sentiment-classifier and see what are their differences.

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aws-lambda-docker-serverless-inference multi-label-sentiment-classifier
1 1
92 17
- -
4.0 1.8
30 days ago about 3 years ago
Jupyter Notebook Jupyter Notebook
MIT No Attribution MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

aws-lambda-docker-serverless-inference

Posts with mentions or reviews of aws-lambda-docker-serverless-inference. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-27.

multi-label-sentiment-classifier

Posts with mentions or reviews of multi-label-sentiment-classifier. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing aws-lambda-docker-serverless-inference and multi-label-sentiment-classifier you can also consider the following projects:

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

Transformer-Explainability - [CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

ganbert-pytorch - Enhancing the BERT training with Semi-supervised Generative Adversarial Networks in Pytorch/HuggingFace

keytotext - Keywords to Sentences

detoxify - Trained models & code to predict toxic comments on all 3 Jigsaw Toxic Comment Challenges. Built using ⚡ Pytorch Lightning and 🤗 Transformers. For access to our API, please email us at [email protected].

jetson-containers - Machine Learning Containers for NVIDIA Jetson and JetPack-L4T

predict-subreddit - NLP model that predicts subreddit based on the title of a post

python-machine-learning-book-3rd-edition - The "Python Machine Learning (3rd edition)" book code repository

huggingpics - 🤗🖼️ HuggingPics: Fine-tune Vision Transformers for anything using images found on the web.

hugging-face-workshop - A 90-minute hands on workshop about Hugging Face on SageMaker.

browser-ml-inference - Edge Inference in Browser with Transformer NLP model