tasksource
nlp-recipes
tasksource | nlp-recipes | |
---|---|---|
3 | 5 | |
129 | 6,020 | |
- | - | |
6.6 | 0.0 | |
21 days ago | over 1 year ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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tasksource
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[D] What are notable advances in NLU?
Technically, BERT (bert-base) is not sota anymore. deberta+MTT-DNN (multi-task learning on many datasets) https://ibm.github.io/model-recycling/ is arguably sota.
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[Discussion] ChatGPT and language understanding benchmarks
LAMA, truthfulQA, MMLU, and many others
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[R] tasksource: Structured Dataset Preprocessing Annotations for Frictionless Extreme Multi-Task Learning and Evaluation (480 tasks+ sota encoder)
Found relevant code at https://github.com/sileod/tasksource + all code implementations here
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?
Neural-Scam-Artist - Web Scraping, Document Deduplication & GPT-2 Fine-tuning with a newly created scam dataset.
ludwig - Low-code framework for building custom LLMs, neural networks, and other AI models
beir - A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.
OpenPrompt - An Open-Source Framework for Prompt-Learning.
dataset-viewer - Lightweight web API for visualizing and exploring any dataset - computer vision, speech, text, and tabular - stored on the Hugging Face Hub
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
deepsegment - A sentence segmenter that actually works!
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.
ccg2lambda - Provide Semantic Parsing solutions and Natural Language Inferences for multiple languages following the idea of the syntax-semantics interface.
link-grammar - The CMU Link Grammar natural language parser
forte - Forte is a flexible and powerful ML workflow builder. This is part of the CASL project: http://casl-project.ai/