nlp-recipes
autonlp
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| nlp-recipes | autonlp | |
|---|---|---|
| 5 | 3 | |
| 6,020 | 680 | |
| - | - | |
| 0.0 | 7.3 | |
| over 1 year ago | about 2 years ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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.
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
autonlp
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Classifying song lyrics with Natural Language Processing and AutoML
In this video, I use AutoNLP, an AutoML product designed by Hugging Face, to train a model that classifies song lyrics according to their genre.
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How I almost won an NLP competition without knowing any Machine Learning
If you want to win a Kaggle competition or to train a model for your business or pleasure, you can get started with AutoNLP here.
- AutoNLP: Faster and easier training and deployments of SOTA NLP models
What are some alternatives?
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OpenPrompt - An Open-Source Framework for Prompt-Learning.
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
huggingface_hub - The official Python client for the Huggingface Hub.
deepsegment - A sentence segmenter that actually works!
MAX-Toxic-Comment-Classifier - Detect 6 types of toxicity in user comments.
pymarl2 - Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios)
kaggle-disaster-tweet-competition - Participating to a Kaggle competition without coding any Machine Learning
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.
clip-as-service - 🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP