nlp-recipes
ludwig

nlp-recipes | ludwig | |
---|---|---|
5 | 3 | |
6,020 | 11,320 | |
- | 0.6% | |
0.0 | 6.1 | |
over 2 years ago | 13 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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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
ludwig
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Show HN: Toolkit for LLM Fine-Tuning, Ablating and Testing
This is a great project, little bit similar to https://github.com/ludwig-ai/ludwig, but it includes testing capabilities and ablation.
questions regarding the LLM testing aspect: How extensive is the test coverage for LLM use cases, and what is the current state of this project area? Do you offer any guarantees, or is it considered an open-ended problem?
Would love to see more progress toward this area!
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Python projects with best practices on Github?
Two random examples I found from 30 seconds of googling: Here’s Netflix using it in their crisis management tool, and here’s Uber using it in their deep learning framework.
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Most Frequent 600 Coding Questions on LeetCode
They list themselves all over the internet as an "open source contributor" to Uber, which as far I can tell is based entirely on... reporting that there was an issue with a favicon. To me, it seems like they'll be cheating anybody who employs them based on this, ahem, "experience". And that feels like the tip of the iceberg.
What are some alternatives?
nlp_course - YSDA course in Natural Language Processing
ai-deadlines - :alarm_clock: AI conference deadline countdowns
OpenPrompt - An Open-Source Framework for Prompt-Learning.
Robo-Semantic-Segmentation - Just a simple semantic segmentation library that I developed to speed up the image segmentation pipeline
ccg2lambda - Provide Semantic Parsing solutions and Natural Language Inferences for multiple languages following the idea of the syntax-semantics interface.
data-structures-and-algorithms - Resources that I used to crack some big tech & startups interviews
deepsegment - A sentence segmenter that actually works!
clip-as-service - 🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
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.
mlnotify - 🔔 No need to keep checking your training - just one import line and you'll know the second it's done.
forte - Forte is a flexible and powerful ML workflow builder. This is part of the CASL project: http://casl-project.ai/
aimet - AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
