Sentence Similarity
sentence-transformers
Safetensors
German
English
multilingual
xlm-roberta
feature-extraction
retrieval
semantic-search
ifc
lca
text-embeddings-inference
Instructions to use Hygros-LCA/bge-m3-ifc-kbob-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Hygros-LCA/bge-m3-ifc-kbob-finetuned with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Hygros-LCA/bge-m3-ifc-kbob-finetuned") 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 sentence_bert_config.json from Hygros-LCA/bge-m3-ifc-kbob-finetuned: direct link, hf CLI and curl.
- Browser
- Download file 53 Bytes
-
https://huggingface.co/Hygros-LCA/bge-m3-ifc-kbob-finetuned/resolve/main/sentence_bert_config.json
- Command line
-
hf download hf://Hygros-LCA/bge-m3-ifc-kbob-finetuned/sentence_bert_config.json
-
curl -L -o sentence_bert_config.json https://huggingface.co/Hygros-LCA/bge-m3-ifc-kbob-finetuned/resolve/main/sentence_bert_config.json
53 Bytes
| { | |
| "max_seq_length": 128, | |
| "do_lower_case": false | |
| } |