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--- |
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language: ["fr", "de"] |
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tags: |
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- feature-extraction |
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- embeddings |
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- sentence-similarity |
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--- |
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# LaBSE for French and German |
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This is a shortened version of [sentence-transformers/LaBSE](https://huggingface.co/sentence-transformers/LaBSE). The model was prepaired with the direct help of [cointegrated](https://huggingface.co/cointegrated), the author of the [LaBSE-en-ru model](https://huggingface.co/cointegrated/LaBSE-en-ru). |
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The current model includes only French and German tokens, and the vocabulary is thus 10% of the original while number of parameters in the whole model is 27% of the original. |
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To get the sentence embeddings, you can use the following code: |
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```python |
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import torch |
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from transformers import AutoTokenizer, AutoModel |
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tokenizer = AutoTokenizer.from_pretrained("EIStakovskii/LaBSE-fr-de") |
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model = AutoModel.from_pretrained("EIStakovskii/LaBSE-fr-de") |
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sentences = ["Wie geht es dir?", "Comment vas-tu?"] |
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encoded_input = tokenizer(sentences, padding=True, truncation=True, max_length=64, return_tensors='pt') |
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with torch.no_grad(): |
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model_output = model(**encoded_input) |
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embeddings = model_output.pooler_output |
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embeddings = torch.nn.functional.normalize(embeddings) |
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print(embeddings) |
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``` |
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## Reference: |
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Fangxiaoyu Feng, Yinfei Yang, Daniel Cer, Narveen Ari, Wei Wang. [Language-agnostic BERT Sentence Embedding](https://arxiv.org/abs/2007.01852). July 2020 |
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License: [https://tfhub.dev/google/LaBSE/1](https://tfhub.dev/google/LaBSE/1) |
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