Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:2836
loss:OnlineContrastiveLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use srikarvar/fine_tuned_model_14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use srikarvar/fine_tuned_model_14 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("srikarvar/fine_tuned_model_14") sentences = [ "No, it doesn't exist in version 5.3.1.", "The `from_dictionary` function requires the following:\n- `data` (Union[dict, Mapping]): A collection of keys linked to values or Python objects.\n- `schema` (Schema, optional): If not given, it will be determined from the Mapping values.\n- `metadata` (Union[dict, Mapping], optional): Optional metadata for the schema (if inferred).", "Stages of photosynthesis", "Version 5.3.1 does not contain it." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K