Sentence Similarity
sentence-transformers
PyTorch
Transformers
mpnet
feature-extraction
text-embeddings-inference
Instructions to use hlyu/mpnet_14710 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use hlyu/mpnet_14710 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("hlyu/mpnet_14710") 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] - Transformers
How to use hlyu/mpnet_14710 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hlyu/mpnet_14710") model = AutoModel.from_pretrained("hlyu/mpnet_14710", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19336188789bf8343f53de0d1e0d50317732089bee6f7384ad40ac4a221377c7
- Size of remote file:
- 211 MB
- SHA256:
- edf23f034ed4b852017440cd5481607828140ce25dc9299610042cb6de2cda8c
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