| --- |
| base_model: unknown |
| library_name: model2vec |
| license: mit |
| model_name: my_classifier_pipeline |
| tags: |
| - embeddings |
| - static-embeddings |
| - sentence-transformers |
| --- |
| |
| # my_classifier_pipeline Model Card |
|
|
| This [Model2Vec](https://github.com/MinishLab/model2vec) model is a fine-tuned version of the [unknown](https://huggingface.co/unknown) Model2Vec model. It also includes a classifier head on top. |
|
|
| ## Installation |
|
|
| Install model2vec using pip: |
| ``` |
| pip install model2vec[inference] |
| ``` |
|
|
| ## Usage |
| Load this model using the `from_pretrained` method: |
| ```python |
| from model2vec.inference import StaticModelPipeline |
| |
| # Load a pretrained Model2Vec model |
| model = StaticModelPipeline.from_pretrained("my_classifier_pipeline") |
| |
| # Predict labels |
| predicted = model.predict(["Example sentence"]) |
| ``` |
|
|
| ## Additional Resources |
|
|
| - [Model2Vec Repo](https://github.com/MinishLab/model2vec) |
| - [Model2Vec Base Models](https://huggingface.co/collections/minishlab/model2vec-base-models-66fd9dd9b7c3b3c0f25ca90e) |
| - [Model2Vec Results](https://github.com/MinishLab/model2vec/tree/main/results) |
| - [Model2Vec Tutorials](https://github.com/MinishLab/model2vec/tree/main/tutorials) |
| - [Website](https://minishlab.github.io/) |
|
|
| ## Library Authors |
|
|
| Model2Vec was developed by the [Minish Lab](https://github.com/MinishLab) team consisting of [Stephan Tulkens](https://github.com/stephantul) and [Thomas van Dongen](https://github.com/Pringled). |
|
|
| ## Citation |
|
|
| Please cite the [Model2Vec repository](https://github.com/MinishLab/model2vec) if you use this model in your work. |
| ``` |
| @article{minishlab2024model2vec, |
| author = {Tulkens, Stephan and {van Dongen}, Thomas}, |
| title = {Model2Vec: Fast State-of-the-Art Static Embeddings}, |
| year = {2024}, |
| url = {https://github.com/MinishLab/model2vec} |
| } |
| ``` |
