Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:2806
loss:TripletLoss
text-embeddings-inference
Instructions to use ainativestudio/locomo-e5-large-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ainativestudio/locomo-e5-large-finetuned with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ainativestudio/locomo-e5-large-finetuned") sentences = [ "What kind of interests do Joanna and Nate share?", "[4:21 pm on 16 July, 2023] John: John scored 40 points in a game last week, his highest ever.", "[2:01 pm on 23 January, 2022] Nate: Thanks! The turtles might be small, but both sure have big personalities. I really reccomend having something like these little guys for times of stress.", "[11:54 am on 2 May, 2022] Joanna: Joanna has been working on some projects and testing dairy-free dessert recipes for friends and family." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "__version__": { | |
| "pytorch": "2.10.0", | |
| "sentence_transformers": "5.5.1", | |
| "transformers": "4.57.6" | |
| }, | |
| "default_prompt_name": null, | |
| "model_type": "SentenceTransformer", | |
| "prompts": { | |
| "document": "", | |
| "query": "" | |
| }, | |
| "similarity_fn_name": "cosine" | |
| } |