marqo
forte
| marqo | forte | |
|---|---|---|
| 1 | 2 | |
| 424 | 236 | |
| - | 0.4% | |
| 10.0 | 3.9 | |
| over 1 year ago | 3 months ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
marqo
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[D] NLP for long document understanding ?
We recently released Marqo which is our approach to tensor search! Feel free to reach out if you'd like to chat about it https://github.com/S2Search/marqo
forte
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[P] How Forte Transforms the Building of ML Solutions with PyTorch into Assembly Lines
Github: https://github.com/asyml/forte Documentation: https://asyml-forte.readthedocs.io/en/latest Technical Report: https://aclanthology.org/2020.emnlp-demos.26/
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Building Modular and Re-purposable NLP Pipelines
Introducing Forte, from the CASL open-source project at Petuum. Forte combines multiple NLP tools to construct an entire NLP pipeline with a few lines of python and extend them to different domains.
What are some alternatives?
marqo - Unified embedding generation and search engine. Also available on cloud - cloud.marqo.ai
DialoGPT - Large-scale pretraining for dialogue
jina - ☁️ Build multimodal AI applications with cloud-native stack
nlp-recipes - Natural Language Processing Best Practices & Examples
jina-financial-qa-search
GODEL - Large-scale pretrained models for goal-directed dialog
ByteDetective - The easiest way to search for images on your desktop 🔎
ludwig - Low-code framework for building custom LLMs, neural networks, and other AI models
sycamore - 🍁 Sycamore is an LLM-powered search and analytics platform for unstructured data.
fondant - Production-ready data processing made easy and shareable
mindflow - 🧠 AI-powered CLI git wrapper, boilerplate code generator, chat history manager, and code search engine to streamline your dev workflow 🌊
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.