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Model: Jarbas/ovos-model2vec-intents-distiluse-base-multilingual-cased-v2
Source: Original Platform

README.md

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+---
+base_model: Jarbas/m2v-256-distiluse-base-multilingual-cased-v2
+library_name: model2vec
+license: mit
+model_name: ovos-model2vec-intents-distiluse-base-multilingual-cased-v2
+tags:
+- embeddings
+- static-embeddings
+- sentence-transformers
+language:
+- en
+- de
+- it
+- pt
+- da
+- ca
+- gl
+- fr
+- es
+- nl
+- eu
+datasets:
+- Jarbas/ovos-llm-augmented-intents
+- Jarbas/ovos-weather-intents
+- Jarbas/music_queries_templates
+- Jarbas/OVOSGitLocalize-Intents
+- Jarbas/ovos_intent_examples
+- Jarbas/ovos-common-query-intents
+---
+
+# model_mul_m2v-256-distiluse-base-multilingual-cased-v2 Model Card
+
+This [Model2Vec](https://github.com/MinishLab/model2vec) model is a fine-tuned version of the [distiluse-base-multilingual-cased-v2](https://huggingface.co/Jarbas/m2v-256-distiluse-base-multilingual-cased-v2) 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("model_mul_m2v-256-distiluse-base-multilingual-cased-v2")
+
+# 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}
+}
+```