Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
Core ML
ONNX
Safetensors
OpenVINO
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use novelcore/model15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use novelcore/model15 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("novelcore/model15") 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:
- 3bc5b00c76182bf14bfad13f989aefe37c791781865d11573e89bb13089f7115
- Size of remote file:
- 134 MB
- SHA256:
- 38d78f5cca85e9bfb60faf70f29d28f0946f3d8caba6f82cc45766e8cdfdc036
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