| --- |
| license: apache-2.0 |
| tags: |
| - setfit |
| - sentence-transformers |
| - text-classification |
| pipeline_tag: text-classification |
| --- |
| |
| # Likang/OSS-Governance |
|
|
| This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves: |
|
|
| 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning. |
| 2. Training a classification head with features from the fine-tuned Sentence Transformer. |
|
|
| ## Usage |
|
|
| To use this model for inference, first install the SetFit library: |
|
|
| ```bash |
| python -m pip install setfit |
| ``` |
|
|
| You can then run inference as follows: |
|
|
| ```python |
| from setfit import SetFitModel |
| |
| # Download from Hub and run inference |
| model = SetFitModel.from_pretrained("Likang/OSS-Governance-Update") |
| # Run inference |
| preds = model(["Let's schedule a meeting to discuss how to onboard new committers!"]) |
| ``` |
|
|
| ## BibTeX entry and citation info |
|
|
| ```bibtex |
| TBA |
| ``` |
|
|
