Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use sentence-transformers/nli-bert-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sentence-transformers/nli-bert-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/nli-bert-large") 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] - Transformers
How to use sentence-transformers/nli-bert-large with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/nli-bert-large") model = AutoModel.from_pretrained("sentence-transformers/nli-bert-large") - Notebooks
- Google Colab
- Kaggle
Commit History
Add exported openvino model 'openvino_model_qint8_quantized.xml' cdac1ef verified
Add new SentenceTransformer model with an openvino backend 25fb067 verified
Add new SentenceTransformer model with an openvino backend 9b20233 verified
Add exported ONNX model 'model_qint8_avx512_vnni.onnx' 8159f5b verified
Add exported ONNX model 'model_qint8_avx512.onnx' bff149d verified
Add exported ONNX model 'model_quint8_avx2.onnx' 35bf90f verified
Add exported ONNX model 'model_qint8_arm64.onnx' add2997 verified
Add exported ONNX model 'model_O4.onnx' dd01f63 verified
Add exported ONNX model 'model_O3.onnx' 35a93a1 verified
Add exported ONNX model 'model_O2.onnx' 47a7954 verified
Add exported ONNX model 'model_O1.onnx' 95330c0 verified
Add new SentenceTransformer model with an onnx backend 7e04677 verified
Update README.md 8a33860
Update README.md 6b6d882
Add new SentenceTransformer model. 4ef143f
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