Sentence Similarity
sentence-transformers
PyTorch
Safetensors
Transformers
German
bert
feature-extraction
gBERT-large
RAG
retrieval augmented generation
STS
MTEB
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use aari1995/German_Semantic_STS_V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use aari1995/German_Semantic_STS_V2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("aari1995/German_Semantic_STS_V2") sentences = [ "Das ist eine glรผckliche Person", "Das ist ein glรผcklicher Hund", "Das ist eine sehr glรผckliche Person", "Heute ist ein sonniger Tag" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use aari1995/German_Semantic_STS_V2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("aari1995/German_Semantic_STS_V2") model = AutoModel.from_pretrained("aari1995/German_Semantic_STS_V2") - Inference
- Notebooks
- Google Colab
- Kaggle
Slightly different output from sentence transformers VS using the transformers library VS deploying the model in torch serve
2
#9 opened over 2 years ago
by
Mihail
Training Dataset
#8 opened over 2 years ago
by
moritzwilke
Vectorization of long text
1
#7 opened almost 3 years ago
by
marcelcramer
"No sentence-transformers model found with name ..."
๐ 2
9
#6 opened almost 3 years ago
by
marcelcramer
Domain adaptation
1
#4 opened almost 3 years ago
by
leobg
Request: DOI
1
#2 opened about 3 years ago
by
KimTang
License missing
๐ 9
4
#1 opened over 3 years ago
by
OliP