Yrag aim to deploy machine-learing model quickly and easily
Project description
YRAG is aimed to build up Machine Learning Application quickly!
This is a simple example package. You can use yrag to write your content.
Package included:
Data Science package
- numpy - 1.18.4
- pandas - 1.0.3
- scipy - 1.4.1
- scikit-learn - 0.23.0
- tensorflow - 2.2.0
- torch - 1.4.0+cpu
- transformers - 2.9.1
Database package
- pymssql - 2.1.4
- PyMySQL - 0.9.3
- redis - 3.5.2
- requests - 2.23.0
Note
- Build package : python setup.py sdist bdist_wheel
- Upload package : python -m twine upload dist/*
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
yrag-0.1.5.tar.gz
(2.9 kB
view details)
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
yrag-0.1.5-py3-none-any.whl
(5.0 kB
view details)
File details
Details for the file yrag-0.1.5.tar.gz.
File metadata
- Download URL: yrag-0.1.5.tar.gz
- Upload date:
- Size: 2.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/49.6.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9dca13d7b2d0fa4f660a31444ae69e2cd32b89f503ca4e424e2b4e91965bf3e7
|
|
| MD5 |
b91f0260ae2532b488323e2a7aeb74bc
|
|
| BLAKE2b-256 |
7d1b03ea74dd1ff08c6f040fd381e495b4d5ea7bcd2d12318ad9976b37d6012c
|
File details
Details for the file yrag-0.1.5-py3-none-any.whl.
File metadata
- Download URL: yrag-0.1.5-py3-none-any.whl
- Upload date:
- Size: 5.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/49.6.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a0932671960723e9fdac51670a58d051ee3d1dc614ee020b529da90b1a8e872b
|
|
| MD5 |
7d6aab353350776194ecf26512f5abef
|
|
| BLAKE2b-256 |
75985e3acef0776d2b459373ce0f6032db0a5f5b9de0d1a528782381bc96c2fd
|
