Sentence Similarity
sentence-transformers
Safetensors
Dutch
xlm-roberta
passage-retrieval
pruned
text-embeddings-inference
Instructions to use ciCic/dutch-english-paraphrase-multilingual-mpnet-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ciCic/dutch-english-paraphrase-multilingual-mpnet-base-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ciCic/dutch-english-paraphrase-multilingual-mpnet-base-v2") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
π³π± dutch-english-paraphrase-multilingual-mpnet-base-v2
This model is a 56.1% smaller version of sentence-transformers/paraphrase-multilingual-mpnet-base-v2 for the Dutch language, created using the mtem-pruner space.
This pruned model should perform similarly to the original model for Dutch language tasks with a much smaller memory footprint. However, it may not perform well for other languages present in the original multilingual model as tokens not commonly used in Dutch were removed from the original multilingual model's vocabulary.
Usage
You can use this model with the Transformers library:
from transformers import AutoModel, AutoTokenizer
model_name = "ciCic/dutch-english-paraphrase-multilingual-mpnet-base-v2"
model = AutoModel.from_pretrained(model_name, trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True, use_fast=True)
Or with the sentence-transformers library:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("ciCic/dutch-english-paraphrase-multilingual-mpnet-base-v2")
Credits: cc @antoinelouis
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