Sentence Similarity
sentence-transformers
PyTorch
distilbert
feature-extraction
text-embeddings-inference
Instructions to use SamTheMar/STM_emb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use SamTheMar/STM_emb with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("SamTheMar/STM_emb") 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
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- 2_Dense/model.safetensors +3 -0
- model.safetensors +3 -0
2_Dense/model.safetensors
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model.safetensors
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oid sha256:135c0b524a8aa64e4039b8755556a9960b1d7ddb6d6b3e1125f9e534963f7ade
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