Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use bachngo/intf_e5_base-5ted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use bachngo/intf_e5_base-5ted with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bachngo/intf_e5_base-5ted") 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:
- 5f077be07abb91ed75b6146001ac8d3218def78d7e8d75e493f696b022c227c5
- Size of remote file:
- 17.1 MB
- SHA256:
- f1cc44ad7faaeec47241864835473fd5403f2da94673f3f764a77ebcb0a803ec
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.