Sentence-transformers/paraphrase

1. What is an example of paraphrase sentence?
2. What do sentence transformers do?
3. How are sentence transformers trained?
4. What is a sentence transformer model?
5. How do you evaluate a sentence in transformers?
6. Which model is best for sentence transformer?
7. What is transformer and examples?
8. What is paraphrase mining?
9. How do Transformers know English?
10. How does sentence Bert work?
11. How do sentence embeddings work?
12. What is the difference between Bert and sentence Bert?
13. What are the transformers fighting for?

What is an example of paraphrase sentence?

Paraphrasing Sentences

Original: Giraffes like Acacia leaves and hay and they can consume 75 pounds of food a day. Paraphrase: A giraffe can eat up to 75 pounds of Acacia leaves and hay every day.

What do sentence transformers do?

Sentence Transformers and other embedding models such as CLIP solve the Task of predicting which data point is similar to the query and which data point or data points are dissimilar to the query. This is different from GPT and BERT style models that complete the Task of predicting a masked out token.

How are sentence transformers trained?

To train a Sentence Transformers model, you need to inform it somehow that two sentences have a certain degree of similarity. Therefore, each example in the data requires a label or structure that allows the model to understand whether two sentences are similar or different.

What is a sentence transformer model?

sentence-transformers is a library that provides easy methods to compute embeddings (dense vector representations) for sentences, paragraphs and images. Texts are embedded in a vector space such that similar text is close, which enables applications such as semantic search, clustering, and retrieval.

How do you evaluate a sentence in transformers?

Evaluate a model based on the similarity of the embeddings by calculating the accuracy of identifying similar and dissimilar sentences. The metrics are the cosine similarity as well as euclidean and Manhattan distance The returned score is the accuracy with a specified metric. The results are written in a CSV.

Which model is best for sentence transformer?

The all-mpnet-base-v2 model provides the best quality, while all-MiniLM-L6-v2 is 5 times faster and still offers good quality. Toggle All models to see all evaluated models or visit HuggingFace Model Hub to view all existing sentence-transformers models.

What is transformer and examples?

Transformers are employed for widely varying purposes. For example, a transformer is often used to reduce the voltage of conventional power circuits to operate low-voltage devices and to raise the voltage from electric generators so that electric power can be transmitted over long distances.

What is paraphrase mining?

Paraphrase mining is the task of finding paraphrases (texts with identical / similar meaning) in a large corpus of sentences. In Semantic Textual Similarity we saw a simplified version of finding paraphrases in a list of sentences. The approach presented there used a brute-force approach to score and rank all pairs.

How do Transformers know English?

It's possible that when Teletraan I was first reactivated and went about scanning earth "life forms" that it also scanned and translated earth languages. It could have also downloaded it into each Transformer as it repaired them, explaining why both the Autobots and Decepticons could speak English right off the bat.

How does sentence Bert work?

Sentence-BERT uses a Siamese network like architecture to provide 2 sentences as an input. These 2 sentences are then passed to BERT models and a pooling layer to generate their embeddings. Then use the embeddings for the pair of sentences as inputs to calculate the cosine similarity.

How do sentence embeddings work?

Embeddings are fixed-length, multi-dimensional vectors that make it possible to extract and manipulate the meaning of the segments they represent, for example by comparing how similar two sentences are to each other semantically.

What is the difference between Bert and sentence Bert?

We explained the cross-encoder architecture for sentence similarity with BERT. SBERT is similar but drops the final classification head, and processes one sentence at a time. SBERT then uses mean pooling on the final output layer to produce a sentence embedding.

What are the transformers fighting for?

The Great War was the first and most violent outburst of fighting on the planet Cybertron, between the newly christened Autobots and Decepticons. It was started by Megatron's initial drive to overthrow the caste system, although this noble goal was corrupted by his jealousy of Orion Pax's ascension to Prime.