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-1.0.1.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-1.0.1-py3-none-any.whl (22.0 kB view details)

Uploaded Python 3

File details

Details for the file DMLP-1.0.1.tar.gz.

File metadata

  • Download URL: DMLP-1.0.1.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-1.0.1.tar.gz
Algorithm Hash digest
SHA256 5d7ec21d98f0b6af3f25f669bed7263af293493b51ebf70ce3860931afcddb06
MD5 8cd5b98d2a6bd1eaadb0eacc9ad719f1
BLAKE2b-256 13fc9d6290e0f6b54791f45952b369cc236260e8cefa5b71ff182d24d230a174

See more details on using hashes here.

File details

Details for the file DMLP-1.0.1-py3-none-any.whl.

File metadata

  • Download URL: DMLP-1.0.1-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-1.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 0eba56e0888a3cf1636cbf9d7105c99c38b30b72a661b9eef3b78eafab7cd61c
MD5 7f7cf90b1dbd70182820e534cb15abfd
BLAKE2b-256 333e032716ab8daa429d985f45f0d246fdb5816e3457914c81ced2eef1c60295

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