Skip to main content

My first Python package

Project description

DMLP

DMLP is a python library for training diffusion model

  • Website:
  • Documentation:
  • Mailing list:
  • Source code:
  • Contributing:
  • Bug reports:

It provides:

  • APIs for constructing and training/fine-tuning text diffusion model
  • Abstract classes for developing models in text diffusion

Installation


On Linux

pip install DMLP==1.0.0

Tutorial

We provide a demo file in at https://github.com/YunhaoLi012/DMLP/blob/torchamp/tests/test_train.py . This script replicate the result of the following paper https://openreview.net/forum?id=bgIZDxd2bM . To run the code, simpily run the following command

CUDA_VISIBLE_DEVICES=0 torchrun test_train.py

Make sure you are in the folder which contains test_train.py file.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

DMLP-1.0.2.tar.gz (18.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

DMLP-1.0.2-py3-none-any.whl (22.0 kB view details)

Uploaded Python 3

File details

Details for the file DMLP-1.0.2.tar.gz.

File metadata

  • Download URL: DMLP-1.0.2.tar.gz
  • Upload date:
  • Size: 18.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.12

File hashes

Hashes for DMLP-1.0.2.tar.gz
Algorithm Hash digest
SHA256 112d5db8686a49ec4b7a9dff972be3681c61370b486e29a589866a1928130e24
MD5 83ee5d5758d76804659d9136482d7364
BLAKE2b-256 697996de10e95d159f5b64aa75b9917a7fc27ddf860a284f10f60bac18a4c57d

See more details on using hashes here.

File details

Details for the file DMLP-1.0.2-py3-none-any.whl.

File metadata

  • Download URL: DMLP-1.0.2-py3-none-any.whl
  • Upload date:
  • Size: 22.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.12

File hashes

Hashes for DMLP-1.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 7b7438f945433a13e4988d873df7b2e76240cedd4e2527382882a71b2e020666
MD5 7269f2d36e10d0fe9309ccb6b236deb6
BLAKE2b-256 56fab27e28bbb7b22d0065000aafa4313da04a70d65cff9e998648b59d07cff2

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page