Sentence Similarity
sentence-transformers
TensorBoard
Safetensors
English
bert
feature-extraction
Generated from Trainer
dataset_size:101762
loss:TripletLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use palusi/sentest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use palusi/sentest with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("palusi/sentest") sentences = [ "Why am I still afraid of the dark?", "What one single change can change a life?", "Why do we have a dark side?", "Why are humans afraid of the dark?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from palusi/sentest: direct link, hf CLI and curl.
- Browser
- Download file 5.62 kB
-
https://huggingface.co/palusi/sentest/resolve/main/training_args.bin
- Command line
-
hf download hf://palusi/sentest/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/palusi/sentest/resolve/main/training_args.bin
5.62 kB
- Xet hash:
- d66f89abd5aba2b530587cc701c46944ec81eb39088ac55c818d548cb6180c28
- Size of remote file:
- 5.62 kB
- SHA256:
- 5ffdf8a6c5238088ca5467590d3fe9d66dfd96a841d5e50b345f615f6431dad0
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