Sentence Similarity
sentence-transformers
Safetensors
English
bert
zephyr
feature-extraction
retrieval
rag
text-embeddings-inference
Instructions to use eoinedge/zephyrproject-docs-embeddings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use eoinedge/zephyrproject-docs-embeddings with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("eoinedge/zephyrproject-docs-embeddings") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "base_model": "sentence-transformers/all-MiniLM-L6-v2", | |
| "train_pairs": 6079, | |
| "eval_pairs": 400, | |
| "epochs": 1, | |
| "batch_size": 32, | |
| "recall_at_5_baseline": 0.63, | |
| "recall_at_5_tuned": 0.86 | |
| } |