Text-Summarization-using-NLP
haystack
| Text-Summarization-using-NLP | haystack | |
|---|---|---|
| 2 | 61 | |
| 40 | 17,908 | |
| - | 2.5% | |
| 0.0 | 9.8 | |
| almost 2 years ago | 7 days 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.
Text-Summarization-using-NLP
haystack
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AI Engineer's Tool Review: Haystack
Are you curious about the NLP/GenAI/RAG framework for developers? Check out my opinionated developer review of Haystack, which emerges as a robust NLP/RAG framework that excels in search and retrieval applications: Read the review.
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7 AI Open Source Libraries To Build RAG, Agents & AI Search
🌟 Haystack on GitHub
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Launch HN: Haystack (YC W21) – Visualize and edit code on an infinite canvas
Did you really have to pick the same name as the Haystack open source AI framework? https://haystack.deepset.ai/ https://github.com/deepset-ai/haystack
It's a very active project and it's confusing to have two projects with the same name. Besides, I don't understand why you'd give a "2D digital whiteboard that automatically draws connections between code as you navigate and edit files" the name haystack.
- The open source LLM framework Haystack is trending on GitHub
- LangChain Is a Black Box
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Haystack DB – 10x faster than FAISS with binary embeddings by default
I was confused for a bit but there is no relation to https://haystack.deepset.ai/
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Release Radar • March 2024 Edition
View on GitHub
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First 15 Open Source Advent projects
4. Haystack by Deepset | Github | tutorial
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Generative AI Frameworks and Tools Every Developer Should Know!
Haystack can be classified as an end-to-end framework for building applications powered by various NLP technologies, including but not limited to generative AI. While it doesn't directly focus on building generative models from scratch, it provides a robust platform for:
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Best way to programmatically extract data from a set of .pdf files?
But if you want an API that you can use to develop your own flow, Haystack from Deepset could be worth a look.
What are some alternatives?
pytextrank - Python implementation of TextRank algorithms ("textgraphs") for phrase extraction
langchain - 🦜🔗 Build context-aware reasoning applications
skweak - skweak: A software toolkit for weak supervision applied to NLP tasks
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
nlu - 1 line for thousands of State of The Art NLP models in hundreds of languages The fastest and most accurate way to solve text problems.
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
LLM-Finetuning-Toolkit - Toolkit for fine-tuning, ablating and unit-testing open-source LLMs.
BentoML - The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!
LLM-Finetuning-Hub - Toolkit for fine-tuning, ablating and unit-testing open-source LLMs. [Moved to: https://github.com/georgian-io/LLM-Finetuning-Toolkit]
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
ReadabilityAnalyserDE - A analyser of German text readability
serve - ☁️ Build multimodal AI applications with cloud-native stack