Sentence Similarity
sentence-transformers
Safetensors
mpnet
feature-extraction
Generated from Trainer
dataset_size:18963
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use Rich740804/st-scale70 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Rich740804/st-scale70 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Rich740804/st-scale70") sentences = [ "If the comatose man had previously expressed a desire to be euthanized in such a situation, respecting his autonomy would support euthanasia.", "If the comatose man had previously expressed a desire for euthanasia in such circumstances, there may be a duty to respect his autonomy, which would support the action.", "If the man is believed to be suffering in his comatose state or there is a significant burden on his family, there may be a duty to alleviate suffering that supports euthanasia.", "As a living being, the rat may warrant a duty of care from humans, which may include providing it with appropriate medical treatment or humane euthanasia in case of suffering." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- babd582eb7a1a5d8f5ee271f45cec304d5a118a095f279faeaf7ca5a47924c08
- Size of remote file:
- 1.06 kB
- SHA256:
- 910cf5dbaaaf2bc4cea5efbe1ecc61775cce0fc384d2bcaec9d177e61c6e9ee7
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