RecBole is developed based on Python and PyTorch for reproducing and developing recommendation algorithms in a unified, comprehensive and efficient framework for research purpose. In the first version, our library includes 53 recommendation algorithms, covering four major categories: General Recommendation, Sequential Recommendation, Context-aware Recommendation and Knowledge-based Recommendation. View RecBole homepage for more information: https://recbole.io
Metadata
Release files for recbole 1.2.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| recbole-1.2.1.tar.gz | 1.9 MB | Without provenance | Details for recbole-1.2.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| recbole-1.2.1-py3-none-any.whl | Python 3 | none | any | Details for recbole-1.2.1-py3-none-any.whl |
Total release size: 4.1 MB
Release files / recbole-1.2.1.tar.gz
| Download URL | recbole-1.2.1.tar.gz |
|---|---|
| Size | 1.9 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.11.3
|
Release files / recbole-1.2.1-py3-none-any.whl
| Download URL | recbole-1.2.1-py3-none-any.whl |
|---|---|
| Size | 2.1 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
9c9948202011f37eb0a7c6768129313f00d6403ad221ec940d5e2d5d5f33a407
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|
BLAKE2b-256 checksum How to use checksums |
abfe7d606cb7cd2b166a36b100cb9435d21014ceee16c192d972deb0976967a8
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.11.3
|
Security for recbole 1.2.1
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