-
Hello,
I am trying to use this inside of a Docker image. I have downloaded the model separately from [here](https://tfhub.dev/google/universal-sentence-encoder-large/5), and I have performed the `p…
-
In addition to word embedding models like GloVe, there are now text embedding models like BERT and Universal Sentence Encoder that work at the level of sentences. These embedding models take an entire…
-
@LamDang j'ai commencé à checker le Universal Encoder Sentence
-
### Background and Feature Description
The `universal-sentence-encoder` model can generate text embeddings, and it depends on TensorFlow Text. Is TensorFlow Text supported?
https://tfhub.dev/googl…
-
It would be really interesting to see graph connections based on a semantic relatedness threshold using embeddings from something like google's Universal Sentence Encoder.
-
Can you please provide the link to the Universal Sentence Encoder model that was used to calculate results for STS tasks? How to fine-tune USE model?
-
Dependent on the length of the documents the universal sentence encoder needs about 30-50 secs to find similar sentences in 10 documents.
For the CNN the lookup table is build by iterating through t…
-
# blog - 日本語Embeddingモデルのベンチマーク比較: OpenAIが圧倒的な精度でリード
日本語の埋め込みモデルを比較するベンチマークを作成し、OpenAIの精度が最も高く、他のモデルに比べて各指標で10%高いことが分かりました。また、他の埋め込みモデルの中で最も精度が高いのはTensorFlowのUniversal Sentence Encoderでした。
[https://…
-
I noticed that if I call
`def save(self, file):`
from the `Top2Vec` class, the embedding model does not get saved.
This is because of the following lines:
```
# do not save sentence encoders, …
-
The idea of using the Universal Sentence Encoder to gather enough training data for CNN classification only makes sense if the documents that are analyzed might include relevant sentences.
If the col…