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While cross encoders have shown better performance than using cosine similarity scores on sentence embeddings, there are no multilingual cross encoders, making this solution only viable for English. E…
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Hi,
I am trying to obtain the semantic similarity between the generated and the ground truth sentence.
I used all these metrics to evaluate the generated sentences (validation dataset):
BLEU 1…
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I am using 'sentence-transformers/all-mpnet-base-v2'. My question is what happens when I encode a text longer than 384 tokens?
Does the model embed sentences in the longer text separately?
If so ho…
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# I'm using Google Colab
s = "would sentiment"
disambiguate(s, algorithm=maxsim, similarity_option='path', keepLemmas=True)
# the same with "may sentiment", "might sentiment", "must sentiment", ...…
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Hello, I have to train a ST model on a very specific task, unfortunately my dataset is not big enough, therefore I was thinking to augment my data using an LLM. As my task is quite specific and demand…
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Hi,
I've been using sentence-transformers for a while, and I really love it - thanks a lot for your work!
I have a question about the best way to compare the semantic relatedness of a bunch of d…
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With this code:
```
from sklearn.cluster import KMeans
num_clusters = 5
clustering_model = KMeans(n_clusters=num_clusters)
clustering_model.fit(corpus_embeddings)
cluster_assignment = cluste…
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Hi Nils,
I have English, Chinese and Indonesian text data for semantic search use case.
I have sentence pairs with different language combinations and similarity score.
I tried pretrained Xlm-r se…
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I load the model and try to predict the similarity between sentence A and sentence B. when I change the order of these sentences (i change the place of sentence A and B and swapped them), i get differ…
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### Description
While trying to run this notebook, https://github.com/microsoft/nlp/blob/master/examples/sentence_similarity/gensen_local.ipynb
I run into this error:
----------------------------…