Sentence Similarity
sentence-transformers
PyTorch
bert
feature-extraction
Generated from Trainer
dataset_size:8408
loss:CosineSimilarityLoss
text-embeddings-inference
Instructions to use kuljeet98/bert-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use kuljeet98/bert-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("kuljeet98/bert-model") sentences = [ "president", "assistante de banque priv e banco santander rio", "worldwide executive vice president corindus a siemens healthineers company", "soporte t cnico superior" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:a32b994f57038e515aac66bf2423ec395b3a21efedf64a1a298dbd19e5f8e99b
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size 470637416
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