browser-ml-inference VS multi-label-sentiment-classifier

Compare browser-ml-inference vs multi-label-sentiment-classifier and see what are their differences.

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browser-ml-inference multi-label-sentiment-classifier
1 1
294 17
- -
0.0 1.8
over 1 year ago about 3 years ago
Jupyter Notebook Jupyter Notebook
Apache License 2.0 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.

browser-ml-inference

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

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 browser-ml-inference and multi-label-sentiment-classifier you can also consider the following projects:

adaptnlp - An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.

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

HugsVision - HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision

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

anime-or-not - NLP model that determines whether a plot is anime enough

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].

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

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

converse - Conversational text Analysis using various NLP techniques

clip-italian - CLIP (Contrastive Language–Image Pre-training) for Italian

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