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--- |
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language: fr |
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tags: |
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- semantic |
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- sentence-transformers |
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- sentence-similarity |
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- fr |
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datasets: |
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- sts |
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--- |
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# French STS |
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## STS dev (french) |
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87.4% |
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## STS test (french) |
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85.8% |
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#### STS pipeline |
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```python |
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!pip install -U sentence-transformers |
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from sentence_transformers import SentenceTransformer |
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model = SentenceTransformer('..model_path..') |
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sentences1 = ["J'aime mon téléphone", |
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"Mon téléphone n'est pas bon.", |
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"Votre téléphone portable est superbe."] |
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|
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sentences2 = ["Est-ce qu'il neige demain?", |
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"Récemment, de nombreux ouragans ont frappé les États-Unis", |
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"Le réchauffement climatique est réel",] |
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embeddings1 = model.encode(sentences1, convert_to_tensor=True) |
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embeddings2 = model.encode(sentences2, convert_to_tensor=True) |
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cosine_scores = util.pytorch_cos_sim(embeddings1, embeddings2) |
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for i in range(len(sentences1)): |
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for j in range(len(sentences2)): |
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print(cosine_scores[i][j])) |
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""" |
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""" |
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``` |
