Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

add CLI support ArgillaTrainer #2809

Closed
davidberenstein1957 opened this issue Apr 28, 2023 · 2 comments
Closed

add CLI support ArgillaTrainer #2809

davidberenstein1957 opened this issue Apr 28, 2023 · 2 comments
Labels
type: enhancement Indicates new feature requests
Milestone

Comments

@davidberenstein1957
Copy link
Member

Is your feature request related to a problem? Please describe.
I want to use CLI!

Describe the solution you'd like

Usage: python -m argilla.tasks.training [OPTIONS]

  Creates a default training task using CLI commands.

Options:
  -n, --name TEXT              The name of the dataset to be used for
                               training.
  -f, --framework TEXT         Choose a framework: transformers, openai,
                               span_marker, setfit or spacy.
  -w, --workspace TEXT         The workspace to be used for training.
  -l, --limit TEXT             The number of record to be used.
  -q, --query TEXT             The query to be used.
  -m, --model TEXT             The modelname or path to be used for training.
  -t, --train-size FLOAT       The train split to be used.
  -s, --seed INTEGER           The random seed number.
  -d, --device INTEGER         The GPU id to be used for training.
  -o, --output-dir TEXT        Output directory for the saved model.
  --update-config-kwargs TEXT  Output directory for the saved model.
  --api-url TEXT               Api url to be used for training.
  --api-key TEXT               Api key to be used for training.
  --help                       Show this message and exit.

Describe alternatives you've considered
N.A.

Additional context
N.A.

@davidberenstein1957 davidberenstein1957 added the type: enhancement Indicates new feature requests label Apr 28, 2023
@alvarobartt
Copy link
Member

alvarobartt commented Apr 28, 2023

To add something else, I think we can map the CLI entry point to be argilla train instead of argilla.tasks.training. And I'd suggest the usage of Typer.

@davidberenstein1957
Copy link
Member Author

I agree.

@frascuchon frascuchon modified the milestones: v1.7, v1.7.0 May 10, 2023
frascuchon added a commit that referenced this issue May 10, 2023
##
[1.7.0](v1.6.0...v1.7.0)

### Added

- add `max_retries` and `num_threads` parameters to `rg.log` to run data
logging request concurrently with backoff retry policy. See
[#2458](#2458) and
[#2533](#2533)
- `rg.load` accepts `include_vectors` and `include_metrics` when loading
data. Closes [#2398](#2398)
- Added `settings` param to `prepare_for_training`
([#2689](#2689))
- Added `prepare_for_training` for `openai`
([#2658](#2658))
- Added `ArgillaOpenAITrainer`
([#2659](#2659))
- Added `ArgillaSpanMarkerTrainer` for Named Entity Recognition
([#2693](#2693))
- Added `ArgillaTrainer` CLI support. Closes
([#2809](#2809))

### Changed

- Argilla quickstart image dependencies are externalized into
`quickstart.requirements.txt`. See
[#2666](#2666)
- bulk endpoints will upsert data when record `id` is present. Closes
[#2535](#2535)
- moved from `click` to `typer` CLI support. Closes
([#2815](#2815))
- Argilla server docker image is built with PostgreSQL support. Closes
[#2686](#2686)
- The `rg.log` computes all batches and raise an error for all failed
batches.
- The default batch size for `rg.log` is now 100.

### Fixed

- `argilla.training` bugfixes and unification
([#2665](#2665))
- Resolved several small bugs in the `ArgillaTrainer`.

### Deprecated

- The `rg.log_async` function is deprecated and will be removed in next
minor release.
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
type: enhancement Indicates new feature requests
Projects
None yet
Development

No branches or pull requests

3 participants