Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
matryoshka
embeddings
Eval Results (legacy)
text-embeddings-inference
Instructions to use hasankursun/matryoshka-embedding-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use hasankursun/matryoshka-embedding-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("hasankursun/matryoshka-embedding-v1") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Download sentence_bert_config.json from hasankursun/matryoshka-embedding-v1: direct link, hf CLI and curl.
- Browser
- Download file 61 Bytes
-
https://huggingface.co/hasankursun/matryoshka-embedding-v1/resolve/main/sentence_bert_config.json
- Command line
-
hf download hf://hasankursun/matryoshka-embedding-v1/sentence_bert_config.json
-
curl -L -o sentence_bert_config.json https://huggingface.co/hasankursun/matryoshka-embedding-v1/resolve/main/sentence_bert_config.json
61 Bytes
| { | |
| "max_seq_length": 8192, | |
| "do_lower_case": false | |
| } |