ClearML/clearml-docs
1
0
Fork 0
mirror of https://github.com/clearml/clearml-docs synced 2025-05-19 03:31:59 +00:00
Code Issues Actions 1 Packages Projects Releases Wiki Activity

Small edits (#748)

Browse Source
This commit is contained in:
pollfly 2024-01-04 10:55:58 +02:00 committed by GitHub
parent 02c7b50c5c
commit fc95f8d84a
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 2 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
docs/guides/frameworks/huggingface/transformers.md
View File

@ -5,7 +5,7 @@ title: Transformers
The [HuggingFace Transformers example](https://github.com/allegroai/clearml/blob/master/examples/frameworks/huggingface/transformers.ipynb) The [HuggingFace Transformers example](https://github.com/allegroai/clearml/blob/master/examples/frameworks/huggingface/transformers.ipynb)
demonstrates how to integrate ClearML into your Transformer's [Trainer](https://huggingface.co/docs/transformers/v4.34.1/en/main_classes/trainer) demonstrates how to integrate ClearML into your Transformer's [Trainer](https://huggingface.co/docs/transformers/v4.34.1/en/main_classes/trainer)
code. The HuggingFace Trainer automatically uses the built-in [`ClearMLCallback`](https://huggingface.co/docs/transformers/v4.34.1/en/main_classes/callback#transformers.integrations.ClearMLCallback) code. The HuggingFace Trainer automatically uses the built-in [`ClearMLCallback`](https://huggingface.co/docs/transformers/v4.34.1/en/main_classes/callback#transformers.integrations.ClearMLCallback)
if the `clearl` package is already installed, to log Transformers models, parameters, scalars, and more. if the `clearml` package is already installed, to log Transformers models, parameters, scalars, and more.
In the example, ClearML is installed and set up in the training environment. This way ClearML can log models, parameters, In the example, ClearML is installed and set up in the training environment. This way ClearML can log models, parameters,
scalars, and more. scalars, and more.

2
docs/webapp/webapp_exp_reproducing.md
View File

@ -4,7 +4,7 @@ title: Reproducing Experiments
Reproduce experiments on local or remote machines in one of the following ways: Reproduce experiments on local or remote machines in one of the following ways:
* Cloning any experiment - Make an exact copy, while maintaining the original experiment * Cloning any experiment - Make an exact copy, while maintaining the original experiment
* Resetting an experiment whose status is not Published - Delete the previous run's logs and output * Resetting an experiment whose status is not *Published* - Delete the previous run's logs and output
After cloning or resetting, enqueue the reset or newly cloned experiment for execution by a worker. After cloning or resetting, enqueue the reset or newly cloned experiment for execution by a worker.