* Feature/v1.1.0 (#6)
Summary of work done in this PR
- Add Data Builder Component
- Add Data Tokenizer Component
- Update Process with Data Builder and Tokenizer
- Create new process pipeline for the data
- Add support for transformers
- Add sample MNLI data versioned by Git LFS
- Add support for MLM
- Update README instructions
- Add: component governance files
- Fix component governance dependency alerts
- update dep for component governance alerts
- Create Github Page with and set theme jekyll-theme-cayman
- Update text classification example
- Update generate_requirements_txt.py
* MT-DNN Feature release v1.0.0
ignore: IDE meta files
add: initial checkin
feat: make package pip installable
doc: add contribution steps and update readme with additional information
fix: wrong file references
add: package dependencies like PyTorch transformer support
fix import statements
feat: add download utils
feat: add download shell script
doc: update readme with testing instructions
doc: add data downloading and processing step
feat: move fit and predict into MTDNN Model
feat: make logger create a new log file each run
remove: fit and predict functions from the pipeline class
update: remove stale references
doc: fit and predict now on the model object
formatting code snippet
doc: add pip install steps
ignore: checkpoints and log files
add: conda file for env generation
feat: docker file support
doc: README for example and data
add: sample data in json lines format
feat: jupyter example
remove: batch_size is controlled by configuration
feat: jupyter notebook
add: license and copyright
add: git lfs track sample data files
data: add sample data file with git lfs
doc: batch_size is now set in config
cleanup
Emmanuel Awa
Sharat Chikkerur
Emmanuel Awa
Microsoft Open Source
microsoft-github-operations[bot]