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.

Usage

You can use this model with the Transformers library:

python

from transformers import AutoModel, AutoTokenizer

model_name = "gbnath/english-bge-m3"
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:

python

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("gbnath/english-bge-m3")

Credits: cc @antoinelouis