A lightweight deep learning framework built from scratch
Project description
matrixflowers
A lightweight deep learning framework built from scratch.
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
matrixflowers-0.1.0.tar.gz
(13.4 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
File details
Details for the file matrixflowers-0.1.0.tar.gz.
File metadata
- Download URL: matrixflowers-0.1.0.tar.gz
- Upload date:
- Size: 13.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
fef67f5af5220b580a95e7262f10077a2cc524f8b51997477f0917331b36e238
|
|
| MD5 |
db34c348b13c991d6f23cb5554f489f6
|
|
| BLAKE2b-256 |
b00fc161570b99f6ad9b43f52460ff7d74285afac9a59b687311e5667aea3b89
|
File details
Details for the file matrixflowers-0.1.0-py3-none-any.whl.
File metadata
- Download URL: matrixflowers-0.1.0-py3-none-any.whl
- Upload date:
- Size: 17.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ed068d388934ebe7afc53eb71a5efcf61c76cc7a651f1b207b3303e63546d650
|
|
| MD5 |
bd4dfc098315177a28726c2b103d086d
|
|
| BLAKE2b-256 |
7e1aef15069659db83673d0aacce3011b3ddc46f4a95130d42e5f9870ee32a2a
|
