sematic VS nlp-recipes

Compare sematic vs nlp-recipes and see what are their differences.

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sematic nlp-recipes
1 2
517 6,007
17.2% 0.7%
9.7 0.0
4 days ago 26 days ago
Python Python
GNU General Public License v3.0 or later 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.


Posts with mentions or reviews of sematic. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-18.


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

We haven't tracked posts mentioning nlp-recipes yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing sematic and nlp-recipes you can also consider the following projects:

rasa - πŸ’¬ Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants

OpenPrompt - An Open-Source Framework for Prompt-Learning.

ludwig - Data-centric declarative deep learning framework

pymarl2 - Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios)

Parrot_Paraphraser - A practical and feature-rich paraphrasing framework to augment human intents in text form to build robust NLU models for conversational engines. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.

forte - Forte is a flexible and powerful ML workflow builder. This is part of the CASL project:

deepsegment - A sentence segmenter that actually works!

autonlp - πŸ€— AutoNLP: train state-of-the-art natural language processing models and deploy them in a scalable environment automatically

link-grammar - The CMU Link Grammar natural language parser

ccg2lambda - Provide Semantic Parsing solutions and Natural Language Inferences for multiple languages following the idea of the syntax-semantics interface.

clip-as-service - πŸ„ Embed/reason/rank images and sentences with CLIP models