Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use Karmukilan/e5-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Karmukilan/e5-base-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Karmukilan/e5-base-v2") 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:
- 18d421e12e59ab0aeb4cef1eb29a504868c33efb491fc6b881ec7842592e8bef
- Size of remote file:
- 438 MB
- SHA256:
- d0d559c47d5f71b1d280b13b62a2657f3e3bc70c0786f9ab91a36545e6a8f693
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