Hub

Release Notes
1. Adds support for dataset filtering (460)(AbhinavTuli)
2. Greatly improves to_tensorflow performance (481) (AbhinavTuli)
3. Benchmarks added for Hub 1.x (486) (benchislett)
4. Fixes a bug that caused issues on windows machines (472)(FayazRahman)
5. Fixes a bug that caused issues with TF 2.4.0 (478) (DebadityaPal)
6. Fixes docker build issue (463) (Darkborderman)
7. Added Chinese readme (458) (EYH0602)
8. Better automatic determination of Dataset mode depending on permissions (466)(edogrigqv2)
9. CoLA dataset uploaded to Hub, upload script added to examples (487)(mynameisvinn)
9. Fixes a bug with dataset slicing (480) (AbhinavTuli)
10. Adds support for custom s3 endpoints (including MinIO) (482) (AbhinavTuli)
11. Adds the ability to set a name to a dataset so it appears better on the visualizer (468) (AbhinavTuli)

Fixes an issue in to_pytorch when using a dataset that the user doesn't own.

Release Notes
- Custom s3storage with 5-10x faster than S3FS
- Faster pytorch dataset with current chunk logic
- Fixed caching with in-memory per process without LMDB
- Better Exception handling for loading a dataset, shape and type checks, casting
- Added examples, tutorials, and better GitHub issue handling
- Add the opportunity to fill in additional information about the dataset such as description, license, citation
- Native support with .compute() in the middle for nested tensors

Contributors include. edogrigqv2 AbhinavTuli mynameisvinn Anselmoo sparkingdark sanchitvj Atom-101

Private dataset support
Improved error handling and exceptions
Test coverage reached 73%->80%
Various bug fixes
Transform speedup ~2x, hence from_x convertors work faster

Fixes some issues with segmentation and RAM issues in transform