Datasaur Dinamic with Hugging Face
Hugging Face
Create a custom project, where you can utilize your data, whether it's pre-labeled or unlabeled.
Now you can enable the Datasaur Dinamic extension by adjusting it in the extension settings.\
Provide the details on the extension.
Define the target text, which is the column selected for data classification.
Set up your preferred label set or question options as a target question (for Row Labeling Projects) or as a label set (for Span Labeling Projects).
Click on “Train” to initiate the training process for the labeled data.
Now you can wait for the model to be deployed. Additionally, you can monitor the updates to your datasets and model on your Hugging Face profile.
After the model is deployed, the extension will display the URL. You can copy this URL and use it with our ML Assisted feature through the Hugging Face provider.\
Automate the rest of the data with ML Assisted
As of now, it is assumed that you have successfully deployed a model on Hugging Face.
Fill all the ML-Assisted Labeling fields by copying and pasting the model name from the Datasaur Dinamic extension or your preferred model. Provide your API token and set the desired confidence score.\
Click “Predict labels” to generate labels for the corresponding rows.
By following these steps, we significantly reduce the time required for labeling the entire dataset, promoting a more efficient and streamlined workflow.
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