Sentence Similarity
sentence-transformers
Safetensors
mpnet
ontology-embedding
hyperbolic-space
hierarchical-reasoning
biomedical-ontology
Generated from Trainer
dataset_size:150000
loss:HierarchyTransformerLoss
text-embeddings-inference
Instructions to use Hui97/OnT-MPNet-go with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Hui97/OnT-MPNet-go with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Hui97/OnT-MPNet-go") sentences = [ "cellular response to stimulus", "response to stimulus", "medial transverse frontopolar gyrus", "biological regulation" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "__version__": { | |
| "sentence_transformers": "3.4.0.dev0", | |
| "transformers": "4.45.2", | |
| "pytorch": "2.5.1+cu124" | |
| }, | |
| "prompts": {}, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine" | |
| } |