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:
- 608904d6fa1738885018e5f614dee35a096dc14ebf7a61823d729ce8d682966c
- Size of remote file:
- 19.2 kB
- SHA256:
- 13a3eb21e90ab7972758ff723548796361ea8a357c807ce923cc0ccb906a3d97
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