Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:211
loss:BatchSemiHardTripletLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use juanpprim/finetuned-bge-base-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use juanpprim/finetuned-bge-base-en with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("juanpprim/finetuned-bge-base-en") sentences = [ "\nName : Casa del Camino\nCategory: Boutique Hotel, Travel Services\nDepartment: Marketing\nLocation: Laguna Beach, CA\nAmount: 842.67\nCard: Team Retreat Planning\nTrip Name: Annual Strategy Offsite\n", "\nName : Gartner & Associates\nCategory: Consulting, Business Services\nDepartment: Legal\nLocation: San Francisco, CA\nAmount: 5000.0\nCard: Legal Consultation Fund\nTrip Name: unknown\n", "\nName : SkillAdvance Academy\nCategory: Online Learning Platform, Professional Development\nDepartment: Engineering\nLocation: Austin, TX\nAmount: 1875.67\nCard: Continuous Improvement Initiative\nTrip Name: unknown\n", "\nName : Innovative Patents Co.\nCategory: Intellectual Property Services, Legal Services\nDepartment: Legal\nLocation: New York, NY\nAmount: 3250.0\nCard: Patent Acquisition Fund\nTrip Name: unknown\n" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download modules.json from juanpprim/finetuned-bge-base-en: direct link, hf CLI and curl.
- Browser
- Download file 349 Bytes
-
https://huggingface.co/juanpprim/finetuned-bge-base-en/resolve/main/modules.json
- Command line
-
hf download hf://juanpprim/finetuned-bge-base-en/modules.json
-
curl -L -o modules.json https://huggingface.co/juanpprim/finetuned-bge-base-en/resolve/main/modules.json
349 Bytes
| [ | |
| { | |
| "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" | |
| } | |
| ] |