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lainlives/english-multilingual-e5-base
english-multilingual-e5-base is a sentence similarity model from lainlives. Use it when you need a score for how close two texts are. It is set up for sentence-transformers. The card lists the license as mit.
This model is a 58.0% smaller version of intfloat/multilingual-e5-base for the English language, created using the mtem-pruner space.
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From the Hugging Face model README
This model is a 58.0% smaller version of intfloat/multilingual-e5-base for the English language, created using the mtem-pruner space.
This pruned model should perform similarly to the original model for English 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 English were removed from the original multilingual model's vocabulary.
You can use this model with the Transformers library:
from transformers import AutoModel, AutoTokenizer
model_name = "lainlives/english-multilingual-e5-base"
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("lainlives/english-multilingual-e5-base")
Credits: cc @antoinelouis