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-mteb.png from alibaba-nlp-community/gte-multilingual-base: direct link, hf CLI and curl.
- Browser
- Download file 281 kB
-
https://huggingface.co/alibaba-nlp-community/gte-multilingual-base/resolve/main/images/mgte-mteb.png
- Command line
-
hf download hf://alibaba-nlp-community/gte-multilingual-base/images/mgte-mteb.png
-
curl -L -o mgte-mteb.png https://huggingface.co/alibaba-nlp-community/gte-multilingual-base/resolve/main/images/mgte-mteb.png
281 kB

- Xet hash:
- 236cc42c4ce638291f85531ef86b89f2c798ea2ce0a7ca0fe422847507266bb5
- Size of remote file:
- 281 kB
- SHA256:
- 05a5368a8f33d6e6d3c2dff495b2c7bcc447f7c5b3462fd55b3d7a680be501a8
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