Sentence Similarity
sentence-transformers
Safetensors
German
English
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use embraceableAI/EMB-1-German-Preview-v-0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use embraceableAI/EMB-1-German-Preview-v-0.1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("embraceableAI/EMB-1-German-Preview-v-0.1") sentences = [ "search_query: i love autotrain", "search_query: huggingface auto train", "search_query: hugging face auto train", "search_query: i love autotrain" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d747ca97fe6e145aef974d51b6921c06a4eed57a0513eb2427235a9af134752
- Size of remote file:
- 17.1 MB
- SHA256:
- e4f7e21bec3fb0044ca0bb2d50eb5d4d8c596273c422baef84466d2c73748b9c
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