Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:1489
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use ElijahDevPH/e5-resume-matcher-mnrl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ElijahDevPH/e5-resume-matcher-mnrl with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ElijahDevPH/e5-resume-matcher-mnrl") sentences = [ "query: Comfortable managing a six-figure monthly admin budget and reporting on spending trends", "passage: Student Information Systems Support\r\nRecent graduate targeting a Student Information Systems Support role, with strong academic projects, structured communication, and eagerness to contribute in fast-paced teams. Comfortable translating requirements into clear deliverables and collaborating across functions.\r\n0", "passage: Inspection Support", "passage: Budget Tracking" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.models.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.models.Pooling" | |
| }, | |
| { | |
| "idx": 2, | |
| "name": "2", | |
| "path": "2_Normalize", | |
| "type": "sentence_transformers.models.Normalize" | |
| } | |
| ] |