sematic
nlp-recipes
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| sematic | nlp-recipes | |
|---|---|---|
| 4 | 5 | |
| 942 | 6,020 | |
| 1.1% | - | |
| 8.7 | 0.0 | |
| 15 days ago | over 1 year ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
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.
sematic
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This Week In Python
sematic – open-source ML pipeline development platform
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What is “production” Machine Learning?
Check us out at sematic.dev, star us on Github, and join us on Discord to discuss production ML.
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Sematic – an open-source ML pipelining tool built by ex-Cruise engineers
Hi all – We are a team of ex ML Infra engineers at Cruise (self-driving cars) and we spent the last few months building Sematic.
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Build on AWS Weekly - S1 E5 - Containers Containers Everywhere
Sematic, an open-source development toolkit for AI/ML: https://github.com/sematic-ai/sematic
nlp-recipes
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Show HN: I turned my microeconomics textbook into a chatbot with GPT-3
https://github.com/topics/automatic-summarization
Microsoft/nlp-recipes lists current NLP tasks that would be helpful for a docs bot: https://github.com/microsoft/nlp-recipes#content
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Show HN: DocsGPT, open-source documentation assistant, fully aware of libraries
https://github.com/topics/automatic-summarization
Though now archived,
> Microsoft/nlp-recipes lists current NLP tasks that would be helpful for a docs bot: https://github.com/microsoft/nlp-recipes#content
NLP Tasks: Text Classification, Named Entity Recognition, Text Summarization, Entailment, Question Answering, Sentence Similarity, Embeddings, Sentiment Analysis, Model Explainability, and Auto-Annotatiom
- ✨ 5 Free Resources for Learning Natural Language Processing with Python 🚀
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Is there any utility software/bot that produces descriptor tags for a Reddit image post using the comments?
I found this (https://github.com/microsoft/nlp-recipes) resource and it has a list of pre-built or easily customizable NLP models that I'm going to try out.
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Building a Aspect based sentiment classification
There is an NLP recipe from Microsoft on ABSA. Have you seen this? https://github.com/microsoft/nlp-recipes/blob/master/examples/sentiment_analysis/absa/absa.ipynb
What are some alternatives?
aqueduct - Aqueduct is no longer being maintained. Aqueduct allows you to run LLM and ML workloads on any cloud infrastructure.
ludwig - Low-code framework for building custom LLMs, neural networks, and other AI models
airy - 💬 Open Source App Framework to build streaming apps with real-time data - 💎 Build real-time data pipelines and make real-time data universally accessible - 🤖 Join historical and real-time data in the stream to create smarter ML and AI applications. - ⚡ Standardize complex data ingestion and stream data to apps with pre-built connectors
OpenPrompt - An Open-Source Framework for Prompt-Learning.
django-prose - Wonderful rich-text editing for your Django project
rasa - 💬 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
clamshell - experimenting with a python based shell
deepsegment - A sentence segmenter that actually works!
python-functown - Helper library for Azure Function programming
pymarl2 - Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios)
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
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.