Easily deploy Transformers models over Lightning
Project description
transformers-lightning
A collection of adapters, datasets, datamodules, callbacks, models, language-modeling techniques, schedulers and optimizers to better integrate the PyTorch Lightning and the Transformers libraries.
Release history Release notifications | RSS feed
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
File details
Details for the file transformers_lightning-0.7.12.tar.gz.
File metadata
- Download URL: transformers_lightning-0.7.12.tar.gz
- Upload date:
- Size: 42.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.0 CPython/3.7.11
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | e9f599b54923b1d5282f1fc2c03ec473e5cae077298df8dc69e65f4cf5165342 |
|
| MD5 | 431689cef02b09a5a42a5a7731b76451 |
|
| BLAKE2b-256 | b99638340d01ca036edbe5b738f687c0334ba321e623d0a1f922f70e89929017 |
File details
Details for the file transformers_lightning-0.7.12-py3-none-any.whl.
File metadata
- Download URL: transformers_lightning-0.7.12-py3-none-any.whl
- Upload date:
- Size: 74.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.0 CPython/3.7.11
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 1c2ad336809aed11a4fe6225e5cd42824d8d83cca3ff7c4428b7821298f6098a |
|
| MD5 | 488d10d27bedd22892b4e444aa0dc250 |
|
| BLAKE2b-256 | ab1ee8ca306cc209040988425425a974e625cebe35f0de2ef44f857c62b7aaa9 |
