Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
Generated from Trainer
dataset_size:557850
loss:StarbucksLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use ielabgroup/Starbucks_STS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ielabgroup/Starbucks_STS with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ielabgroup/Starbucks_STS") sentences = [ "A dog is in the water.", "The woman is wearing green.", "The dog is rolling around in the grass.", "A brown dog swims through water outdoors with a tennis ball in its mouth." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download config_sentence_transformers.json from ielabgroup/Starbucks_STS: direct link, hf CLI and curl.
- Browser
- Download file 201 Bytes
-
https://huggingface.co/ielabgroup/Starbucks_STS/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://ielabgroup/Starbucks_STS/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/ielabgroup/Starbucks_STS/resolve/main/config_sentence_transformers.json
201 Bytes
| { | |
| "__version__": { | |
| "sentence_transformers": "3.1.1", | |
| "transformers": "4.44.2", | |
| "pytorch": "2.4.1+cu121" | |
| }, | |
| "prompts": {}, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": null | |
| } |