80fcb86f6b
Model: Jarbas/ovos-model2vec-intents-distiluse-base-multilingual-cased-v2 Source: Original Platform
76 lines
2.2 KiB
Markdown
76 lines
2.2 KiB
Markdown
---
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base_model: Jarbas/m2v-256-distiluse-base-multilingual-cased-v2
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library_name: model2vec
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license: mit
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model_name: ovos-model2vec-intents-distiluse-base-multilingual-cased-v2
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tags:
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- embeddings
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- static-embeddings
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- sentence-transformers
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language:
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- en
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- de
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- it
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- pt
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- da
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- ca
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- gl
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- fr
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- es
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- nl
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- eu
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datasets:
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- Jarbas/ovos-llm-augmented-intents
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- Jarbas/ovos-weather-intents
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- Jarbas/music_queries_templates
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- Jarbas/OVOSGitLocalize-Intents
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- Jarbas/ovos_intent_examples
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- Jarbas/ovos-common-query-intents
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---
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# model_mul_m2v-256-distiluse-base-multilingual-cased-v2 Model Card
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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.
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## Installation
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Install model2vec using pip:
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```
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pip install model2vec[inference]
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```
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## Usage
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Load this model using the `from_pretrained` method:
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```python
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from model2vec.inference import StaticModelPipeline
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# Load a pretrained Model2Vec model
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model = StaticModelPipeline.from_pretrained("model_mul_m2v-256-distiluse-base-multilingual-cased-v2")
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# Predict labels
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predicted = model.predict(["Example sentence"])
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```
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## Additional Resources
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- [Model2Vec Repo](https://github.com/MinishLab/model2vec)
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- [Model2Vec Base Models](https://huggingface.co/collections/minishlab/model2vec-base-models-66fd9dd9b7c3b3c0f25ca90e)
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- [Model2Vec Results](https://github.com/MinishLab/model2vec/tree/main/results)
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- [Model2Vec Tutorials](https://github.com/MinishLab/model2vec/tree/main/tutorials)
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- [Website](https://minishlab.github.io/)
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## Library Authors
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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).
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## Citation
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Please cite the [Model2Vec repository](https://github.com/MinishLab/model2vec) if you use this model in your work.
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```
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@article{minishlab2024model2vec,
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author = {Tulkens, Stephan and {van Dongen}, Thomas},
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title = {Model2Vec: Fast State-of-the-Art Static Embeddings},
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year = {2024},
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url = {https://github.com/MinishLab/model2vec}
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}
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``` |