Contents

deeplake 3.6.14

0

Activeloop Deep Lake

Deep Lake is a Database for AI powered by a unique storage format optimized for deep-learning and Large Language Model (LLM) based applications. It simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage for all workloads, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more.

Stars: 6568, Watchers: 6568, Forks: 504, Open Issues: 59

The activeloopai/deeplake repo was created 3 years ago and the last code push was 2 hours ago.
The project is extremely popular with a mindblowing 6568 github stars!

How to Install deeplake

You can install deeplake using pip

pip install deeplake

or add it to a project with poetry

poetry add deeplake

Package Details

Author
activeloop.ai
License
MPL-2.0
Homepage
PyPi
https://pypi.org/project/deeplake/
GitHub Repo
https://github.com/activeloopai/deeplake

Classifiers

No  deeplake  pypi packages just yet.

Errors

A list of common deeplake errors.

Code Examples

Here are some deeplake code examples and snippets.

GitHub Issues

The deeplake package has 59 open issues on GitHub

  • Data fix
  • [Tiny] Removed reporting when importing deeplake
  • [BUG] Possibly unsafe conversion of DatasetDiff instance to bytes
  • Better metadata search
  • [BUG] Issue with ImageNet training set.
  • [BUG] poetry add deeplake hangs - pip works fine
  • Create SECURITY.md
  • skip visualizer for python3.11
  • [AL-2272] Concurrent writes
  • Indexing deeplake
  • Added support for audio/video support in hub.ingest
  • [FEATURE] Redis storage provider

See more issues on GitHub

Related Packages & Articles

datasets 2.14.2

HuggingFace community-driven open-source library of datasets

nlp 0.4.0

HuggingFace/NLP is an open library of NLP datasets.

pytorch-lightning 2.0.6

PyTorch Lightning is the lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate.

onnx 1.14.0

Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both deep learning and traditional ML. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types. Currently we focus on the capabilities needed for inferencing (scoring).

kornia 0.6.12

Open Source Differentiable Computer Vision Library for PyTorch

thinc 8.1.10

A refreshing functional take on deep learning, compatible with your favorite libraries