Skip to content

Changed type in the sklearn section of the readme #19

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.

Sign up for GitHub

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

Merged
merged 2 commits into from
Sep 5, 2022
Merged

Changed type in the sklearn section of the readme #19

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
4466f8a
Changed type in the sklearn section of the readme
Sep 5, 2022
7d2a26a
Update README.md
Sep 5, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -122,7 +122,7 @@ Alternatively, you can `rsdk push <path-to-your-file>` via CLI, given that you h

### Adapters

#### 🤗 Hugging Face
#### Hugging Face
Transformers are great, but often times, you want to finetune them for your downstream task. With *refinery*, you can do so easily by letting the SDK build the dataset for you that you can use as a plug-and-play base for your training:

```python
Expand Down Expand Up @@ -179,7 +179,7 @@ trainer.save_model("path/to/model")
You can use *refinery* to directly pull data into a format you can apply for building [sklearn](https://github.com/scikit-learn/scikit-learn) models. This can look as follows:

```python
from refinery.adapter.embedders import build_classification_dataset
from refinery.adapter.sklearn import build_classification_dataset
from sklearn.tree import DecisionTreeClassifier

data = build_classification_dataset(client, "headline", "__clickbait", "distilbert-base-uncased")
Expand Down