notes
docarray
| notes | docarray | |
|---|---|---|
| 2 | 32 | |
| 0 | 2,748 | |
| - | 1.5% | |
| 3.8 | 9.2 | |
| about 1 year ago | 4 days ago | |
| Jupyter Notebook | Python | |
| - | 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.
notes
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A multimedia data wrangler's dream, or just hype? 🤔
I've read about Docarray in github last week and it mentioned how it promises to handle complex, mixed and nested multimedia data with ease. I’m curious to hear from those who actually used it or have experienced something similar. So far, Docarray seems very promising. It's able to ingest data from multiple sources, including images, videos, text, and audio.
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Announcing DocArray v2
You can find our rewrite announcement blog post here
docarray
- DocArray – Represent, send, and store multimodal data for ML
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Some questions about multimodal data.
I’ve heard of DocArray, a library for multimodal data in transit and Pytorch Lightning which is also a tool for multimodal data. These two sound like a promising solution, but I’m not sure how to use it with databases or cloud storage. Do I need to install any additional packages or dependencies?
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Trying to create an AI recommender system that’s also ad-free video streaming.
I'm considering using these tools for a recommender system for analyzing text data like user reviews: DocArray and the EZ-MMLA Toolkit. Can anyone share their experience with the DocArray and EZ-MMLA Toolkit? I would love to hear about others' experiences before making a final decision.
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do you know any systems that can handle multimodal data fusion and representation learning?
I have been thinking about trying out DocArray and the EZ-MMLA Toolkit .. Has anyone had experience with these two projects?? Let me know what you think!
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I plan to build my own AI powered search engine for my portfolio. Do you know ones that are open-source?
For some alternatives, I know there’s DocArray where you can handle text, image and audio data. is basically a toolbox for multimodal data and then there should be Haystack which is also let you build search systems and also has to do something with Transformers and LLMs.
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A Guide to Using OpenTelemetry in Jina for Monitoring and Tracing Applications
DocArray to manipulate data and interact with the storage backend using document store.
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This week(s) in DocArray
It's already been two weeks since the last alpha release of DocArray v2. And since then a lot has happened — we've merged features we're really proud of, and we've cried tears of joy and misery trying to coerce Python into doing what we want. If you want to learn about interesting Python edge cases or follow the advancement of DocArray v2 development then you’ve come to the right place in this blog post!
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Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models
The German Fashion12k dataset is available for free use by the Jina AI community. After logging into Jina AI Cloud, you can download it directly in DocArray format:
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Want to Search Inside Videos Like a Pro? CLIP-as-service Can Help
Jina AI’s DocArray library
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Looking for open source projects in Machine Learning and Data Science
You could try spaCy. This is the brains of the operation - an open-source NLP library for advanced NLP in Python. Another is DocArray - It's built on top of NumPy and Dask, and good for preprocessing, modeling, and analysis of text data.
What are some alternatives?
Milvus - A cloud-native vector database, storage for next generation AI applications
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
bootcamp - Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.
kaggle-environments
imodels - Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
discoart - 🪩 Create Disco Diffusion artworks in one line
habitat-sim - A flexible, high-performance 3D simulator for Embodied AI research.
nn - 🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
habitat-lab - A modular high-level library to train embodied AI agents across a variety of tasks and environments.
img2dataset - Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine.
dataqa - Labelling platform for text using weak supervision.
Gorgonia - Gorgonia is a library that helps facilitate machine learning in Go.