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:
- 8dc243e0d5c94a2caef67dddbc38ead2d8a7d99d4ea769b82bf921b2c77d5aee
- Size of remote file:
- 950 MB
- SHA256:
- ac7de8c73b36a8f7211fc814382fb2fd8737ecccf51b3a631d87daf7fec0bc76
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