Sentence Similarity
sentence-transformers
Safetensors
German
bert
passage-retrieval
pruned
text-embeddings-inference
Instructions to use ferrisS/german-english-multilingual-e5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ferrisS/german-english-multilingual-e5-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ferrisS/german-english-multilingual-e5-small") sentences = [ "Das ist eine glückliche Person", "Das ist ein glücklicher Hund", "Das ist eine sehr glückliche Person", "Heute ist ein sonniger Tag" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ferrisS/german-english-multilingual-e5-small: direct link, hf CLI and curl.
- Browser
- Download file 3.35 MB
-
https://huggingface.co/ferrisS/german-english-multilingual-e5-small/resolve/main/tokenizer.json
- Command line
-
hf download hf://ferrisS/german-english-multilingual-e5-small/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ferrisS/german-english-multilingual-e5-small/resolve/main/tokenizer.json
3.35 MB
File too large to display, you can check the raw version instead.