Sentence Similarity
sentence-transformers
Safetensors
German
llama
text-embeddings
german
retrieval
lora
embedding-model
Eval Results (legacy)
text-embeddings-inference
Instructions to use mayflowergmbh/smollm3-3b-german-embed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mayflowergmbh/smollm3-3b-german-embed with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mayflowergmbh/smollm3-3b-german-embed") sentences = [ "Was ist die Hauptstadt von Deutschland?", "Berlin ist die Hauptstadt von Deutschland.", "München ist eine Stadt in Bayern.", "Paris ist die Hauptstadt von Frankreich." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download sentence_bert_config.json from mayflowergmbh/smollm3-3b-german-embed: direct link, hf CLI and curl.
- Browser
- Download file 57 Bytes
-
https://huggingface.co/mayflowergmbh/smollm3-3b-german-embed/resolve/main/sentence_bert_config.json
- Command line
-
hf download hf://mayflowergmbh/smollm3-3b-german-embed/sentence_bert_config.json
-
curl -L -o sentence_bert_config.json https://huggingface.co/mayflowergmbh/smollm3-3b-german-embed/resolve/main/sentence_bert_config.json
57 Bytes
| { | |
| "max_seq_length": 512, | |
| "do_lower_case": false | |
| } |