AugLy
jina
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AugLy | jina | |
---|---|---|
14 | 126 | |
4,898 | 19,884 | |
0.5% | 0.9% | |
6.0 | 9.2 | |
28 days ago | 8 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | 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.
AugLy
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Meta's A.I. exodus: Top talent quits as lab tries to keep pace with rivals
Their recent effort to generate training data for spotting stuff that includes unsanctioned narratives comes to mind. https://github.com/facebookresearch/AugLy
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Next steps for after classification
Data augmentation is usually helpful: https://github.com/facebookresearch/AugLy
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The hand-picked selection of the best Python libraries released in 2021
AugLy.
- Prefer volume or quality for BERT-based Text classification model
- Augly - An augmentation library for audio, image, video, and text from facebook
- [D] What's the best method to generate synthetic data for an image with text? Small dataset
- AugLy is opensourse now.
- Facebook is open-sourcing AugLy, a library that uses data augmentations to evaluate and improve ML models
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Integration test: Complexity of privacy-preserving bird call bio-sensor for distributed ecological monitoring?
Some of the technologies which could be integrated include differential privacy, distributed online machine learning, misinformation resilience and multi-party computation, all within the context of smart contracts and bioinformatics.
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[N] Facebook AI Open Sources AugLy: A New Python Library For Data Augmentation To Develop Robust Machine Learning Models
Facebook Blog: https://ai.facebook.com/blog/augly-a-new-data-augmentation-library-to-help-build-more-robust-ai-models/
jina
- Jina.ai: Self-host Multimodal models
- FLaNK Stack Weekly for 30 Oct 2023
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Cross data type search that wasn’t supported well using Elasticsearch
Jina mainly because of their use of neural networks and AI.
- Recommend a Lightweight Launcher with Nested Folders
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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?
Jina - It’s an open-source project where you can build search engines. Well maybe not no code but it claims that you only need a few lines of code for creating projects. The project supports semantic, text, image, audio, and video search. What I’m also interested in is with their neural search and generative AI. I’m also interested in the amount of github repo that they have. I have this on my radar since this is also something I was interested in.
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How can we match images in our database?
Do you guys have any ideas how we can match images on our database? We’re working on a project that about matching images on our database. We were trying to use SIFT and some other similar methods, but for some reason, nothing doesn’t seem to be working that well. Does anyone have any suggestions for the most effective way to do this? Maybe some open-source solutions like HuggingFace or Jina AI? We just want to make sure our image matching is correct and that part’s been a bit of a struggle on our part.
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Can AI 3D model search engines be a thing this year?
The tech lets you find 3D models without sifting through tons of text - An information retrieval framework does the heavy lifting and compares models to each other, no descriptions or keywords needed.
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Any MLOps platform you use?
Jina AI -They offer a neural search solution that can help build smarter, more efficient search engines. They also have a list of cool github repos that you can check out. Similar to Vertex AI, they have image classification tools, NLPs, fine tuners etc.
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This week(s) in DocArray
Well, it's not exactly a new feature, but we've been working on early support for DocArray v2 in Jina.
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Multi-model serving options
Jina let’s you serve all of your models through the same Gateway while deploying them as individual microservices. You can also tie your models together in a pipeline if needed. Also some nice ML focussed features such as dynamic batching.
What are some alternatives?
imgaug - Image augmentation for machine learning experiments.
Weaviate - Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
speechbrain - A PyTorch-based Speech Toolkit
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.
PySyft - Perform data science on data that remains in someone else's server
dalle-flow - 🌊 A Human-in-the-Loop workflow for creating HD images from text
BlenderProc - A procedural Blender pipeline for photorealistic training image generation
whoogle-search - A self-hosted, ad-free, privacy-respecting metasearch engine
Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]
es-clip-image-search - Sample implementation of natural language image search with OpenAI's CLIP and Elasticsearch or Opensearch.
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
growthbook - Open Source Feature Flagging and A/B Testing Platform