Shows the model's identity and the settings inference will run under: pinned revision, embedding dimensions, backend, and thread count.
Usage
# S3 method for class 'sbert_model'
print(x, ...)Examples
# Pinned models that can be loaded and printed.
models()
#> model dimensions max_tokens languages
#> 1 all-MiniLM-L6-v2 384 256 English
#> 2 all-MiniLM-L12-v2 384 128 English
#> 3 paraphrase-MiniLM-L3-v2 384 128 English
#> 4 multi-qa-MiniLM-L6-cos-v1 384 512 English
#> 5 paraphrase-multilingual-MiniLM-L12-v2 384 128 50+ languages
#> 6 all-mpnet-base-v2 768 384 English
#> 7 paraphrase-multilingual-mpnet-base-v2 768 128 50+ languages
#> 8 bge-small-en-v1.5 384 512 English
#> 9 bge-base-en-v1.5 768 512 English
#> 10 multilingual-e5-small 384 512 100+ languages
#> 11 nomic-embed-text-v1.5 768 8192 English
#> 12 jina-embeddings-v2-small-en 512 8192 English
#> 13 mxbai-embed-large-v1 1024 512 English
#> 14 potion-base-8M 256 1000000 English
#> size_mb
#> 1 90.9
#> 2 133.6
#> 3 69.5
#> 4 90.9
#> 5 479.4
#> 6 436.3
#> 7 1119.2
#> 8 133.8
#> 9 436.5
#> 10 487.4
#> 11 548.0
#> 12 130.5
#> 13 1337.6
#> 14 30.9
# \donttest{
if (interactive()) {
print(load_model())
}
# }