Sentence Similarity
sentence-transformers
Safetensors
mpnet
feature-extraction
Generated from Trainer
dataset_size:178829
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use DashReza7/all-mpnet-base-v2_FINETUNED with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use DashReza7/all-mpnet-base-v2_FINETUNED with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("DashReza7/all-mpnet-base-v2_FINETUNED") sentences = [ "who was actor larry parks", "American stage and movie actor.e eventually did so in tears, only to be blacklisted anyway.", "A possum (plural form: possums) is any of about 70 small-to medium-sized arboreal marsupial species native to Australia, New Guinea, and Sulawesi (and introduced to New Zealand and China). The common brushtail possum was introduced to New Zealand by European settlers in an attempt to establish a fur industry. There are no native predators of the possum in New Zealand, so its numbers in New Zealand have risen to the point where it is considered a serious pest.", "A document used to change one or more minor provisions of a living trust or joint living trust as an alternative to preparing a new living trust." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K