Pytorch model for generating fidelity agnostic synthetic data
Project description
The author of this package has not provided a project description
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
fasd-0.1.0.tar.gz
(12.9 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
fasd-0.1.0-py3-none-any.whl
(12.1 kB
view details)
File details
Details for the file fasd-0.1.0.tar.gz.
File metadata
- Download URL: fasd-0.1.0.tar.gz
- Upload date:
- Size: 12.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.10.16
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8b825d67b6ba91a0a8b2c796d7a7b9447a8d1616cf0e0dcf6e4ee8624cf33224
|
|
| MD5 |
e245c1391c4312f55d9476b8778612b2
|
|
| BLAKE2b-256 |
46ae6be4566ea7220d054522f796a1affbb530da888e610c6a044cde8234af3a
|
File details
Details for the file fasd-0.1.0-py3-none-any.whl.
File metadata
- Download URL: fasd-0.1.0-py3-none-any.whl
- Upload date:
- Size: 12.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.10.16
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
e88f3607e1b4ad5a02fdfec6e17f68935f44f7acafc64180be0f9c56ac42e313
|
|
| MD5 |
81586a2da37858cce7b6867b88f28e79
|
|
| BLAKE2b-256 |
3477aeb5299a988dfbe865e096cf6217aa83457ad700cc937ad20fe39a1fdfa6
|
