ContrXT
nlp-recipes
| ContrXT | nlp-recipes | |
|---|---|---|
| 1 | 5 | |
| 24 | 6,020 | |
| - | - | |
| 0.0 | 0.0 | |
| almost 2 years ago | over 1 year ago | |
| Python | Python | |
| GNU General Public License v3.0 only | MIT License |
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ContrXT
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?
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OpenPrompt - An Open-Source Framework for Prompt-Learning.
argilla - Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency.
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refinery - The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.
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.