MLOpsManufacturing
nlp-recipes
| MLOpsManufacturing | nlp-recipes | |
|---|---|---|
| 1 | 5 | |
| 17 | 6,020 | |
| - | - | |
| 3.2 | 0.0 | |
| 7 months ago | over 1 year ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
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MLOpsManufacturing
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Virtual Network architecture 1 - Do I need virtual network?
Our team is proud of contributing to open source software assets and Microsoft platform that are broadly available. In every project, we create reusable and sharable software assets that can be widely applicable with the agreement of the enterprise clients. Our team practices growth mindset by trying new things and learning from others, and then reuse the learnings and create shared software assets. One examle is Azure-Samples/MLOpsManufacturing created with learnings from multiple projects. As we work more engagements with more clients, more and more other developers can reuse the assets and do not need to spend months designing network security architectures.
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?
kicad-parts-placer - Auto place components into pcbnew from a centroid file. Useful for making pogo pin test jigs.
ludwig - Low-code framework for building custom LLMs, neural networks, and other AI models
openvmp-parts-gobilda - OpenVMP parts that can be purchased from goBILDA
OpenPrompt - An Open-Source Framework for Prompt-Learning.
ERPNext - Free and Open Source Enterprise Resource Planning (ERP)
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
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
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