Sentence Similarity
sentence-transformers
PyTorch
Transformers
mpnet
feature-extraction
text-embeddings-inference
Instructions to use scaperex/SetFitTest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use scaperex/SetFitTest with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("scaperex/SetFitTest") 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 scaperex/SetFitTest with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("scaperex/SetFitTest") model = AutoModel.from_pretrained("scaperex/SetFitTest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 40e893edbf9f1f3cde1a07d0f97f8d357e7e1d7f30123a1a600d647ad01ba122
- Size of remote file:
- 438 MB
- SHA256:
- 66ee1ad629ebe70ec445ed0ea5bd808a2a2dde9a1ef30c96634df1a7a6d1af8c
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