This release is a pre-release and may not be stable for production use.
RecStudio is a modular, efficient, unified, and comprehensive recommendation library based on PyTorch.We divide all the models into 3 basic classes according to the number of towers: TowerFree, ItemTower, TwoTower, and cover models in 4 tasks: General Recommendation, Sequential Recommendation, Knowledge-based Recommendation, Social-Network-based Recommendation. View github page: https://github.com/ustcml/RecStudio
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file recstudio-0.0.2a1.tar.gz.
File metadata
- Download URL: recstudio-0.0.2a1.tar.gz
- Upload date:
- Size: 97.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/4.0.1 CPython/3.9.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
36ff4855f76f1d3b7e260e2b8fa9f73b6b97d8ee8ebc4709fe652ac00835b6c1
|
|
| MD5 |
d5402c7cf7ee86ff49e18aada86d0407
|
|
| BLAKE2b-256 |
3d807eebc17b878ee879f6718b5c6ebb80634b5987fe4ec0844387ac1e03d3c8
|
File details
Details for the file recstudio-0.0.2a1-py3-none-any.whl.
File metadata
- Download URL: recstudio-0.0.2a1-py3-none-any.whl
- Upload date:
- Size: 131.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/4.0.1 CPython/3.9.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d6043f730ce810fa4fea1d1090787593cd298de87bc029aaaaa88527c526f6f6
|
|
| MD5 |
56b36cee625cb9caa14280def6f2a54c
|
|
| BLAKE2b-256 |
d5f6d80d3ddea33ea1c263c9cf5212cca9ccaff0852ff06e5d5de87dc99f23ba
|