Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dataset_size:100K<n<1M
loss:SoftmaxLoss
text-embeddings-inference
Instructions to use emonnsl/embed_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use emonnsl/embed_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("emonnsl/embed_model") sentences = [ "সব কথার মিল আছে।", "অন্য সবার মতো একই কাজ করেছেন।", "কাজের জন্য কোনও টাকা বরাদ্দ নেই।", "তার মাসিক আয় কমে গেছে।" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea6336eb6b785a94d6f0d7a10f31939cc3ffa733cc62e76f133751e8a43bf5df
- Size of remote file:
- 1.06 kB
- SHA256:
- bc860671547306498e813344e7c8ef336853b3c5de1914171e905bbac785c2b7
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