keyphrase mpnet v1 EU AI Act Compliance Profile

keyphrase-mpnet-v1

This is a sentence-transformers model specialized for phrases: It maps phrases to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search. In the original paper, this model is used for calculating semantic-based evaluation metrics of keyphrase models.

This model is based on sentence-transformers/all-mpnet-base-v2 and further fine-tuned on 1 million keyphrase data with SimCSE.

Citing & Authors

Paper: KPEval: Towards Fine-grained Semantic-based Keyphrase Evaluation

Usage (Sentence-Transformers)

Using this model becomes easy when you have sentence-transformers installed:

Then you can use the model like this:

from sentence_transformers import SentenceTransformer
phrases = ["information retrieval", "text mining", "natural language processing"]

model = SentenceTransformer('uclanlp/keyphrase-mpnet-v1')
embeddings = model.encode(phrases)
print(embeddings)

Usage (HuggingFace Transformers)

Without sentence-transformers, you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the c

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