Sentence Similarity
sentence-transformers
Safetensors
Transformers
gte
mteb
multilingual
text-embeddings-inference
Eval Results (legacy)
Instructions to use alibaba-nlp-community/gte-multilingual-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use alibaba-nlp-community/gte-multilingual-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("alibaba-nlp-community/gte-multilingual-base") 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] - Transformers
How to use alibaba-nlp-community/gte-multilingual-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("alibaba-nlp-community/gte-multilingual-base") model = AutoModel.from_pretrained("alibaba-nlp-community/gte-multilingual-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download images/mgte-retrieval.png from alibaba-nlp-community/gte-multilingual-base: direct link, hf CLI and curl.
- Browser
- Download file 356 kB
-
https://huggingface.co/alibaba-nlp-community/gte-multilingual-base/resolve/main/images/mgte-retrieval.png
- Command line
-
hf download hf://alibaba-nlp-community/gte-multilingual-base/images/mgte-retrieval.png
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curl -L -o mgte-retrieval.png https://huggingface.co/alibaba-nlp-community/gte-multilingual-base/resolve/main/images/mgte-retrieval.png
356 kB

- Xet hash:
- 0bf196aaf58cb75556011ee60a16ef67bd5aa1b774bc3203fc218b0d3f6852ad
- Size of remote file:
- 356 kB
- SHA256:
- 1581dc1f0e6210008130ad03bc392f5badda32dc8a0e9ccd21cf30a37b45b5fc
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