Sentence Similarity
sentence-transformers
PyTorch
English
bert
feature-extraction
text-embeddings-inference
Instructions to use rethem-expeditecommerce/MiniLM-L6-mlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rethem-expeditecommerce/MiniLM-L6-mlm with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("rethem-expeditecommerce/MiniLM-L6-mlm") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 138d5af9f7e311bbbc4c1b64bf0649a36706579d4bd8123ff8e4bd19bbc31319
- Size of remote file:
- 90.9 MB
- SHA256:
- c981060de69701ca3d54dfe9dde67ef80e0fb04b499c634ce5eb7d7558d5feab
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.