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Browse files- README.md +3 -23
- model.safetensors +2 -2
- pipeline.skops +2 -2
- tokenizer.json +2 -2
README.md
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base_model: unknown
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library_name: model2vec
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license: mit
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model_name:
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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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datasets:
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- Jarbas/ovos_intents_train
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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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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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---
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#
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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.
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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("
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# Predict labels
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predicted = model.predict(["Example sentence"])
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base_model: unknown
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library_name: model2vec
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license: mit
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model_name: model_mul_m2v-256-LaBSE
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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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---
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# model_mul_m2v-256-LaBSE Model Card
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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.
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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-LaBSE")
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# Predict labels
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predicted = model.predict(["Example sentence"])
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model.safetensors
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pipeline.skops
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tokenizer.json
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