Sentence Similarity
sentence-transformers
Safetensors
English
mpnet
feature-extraction
semantic-search
embeddings
fine-tuned
atles
echo
personal-knowledge
Eval Results (legacy)
text-embeddings-inference
Instructions to use spartan8806/echo-tuned-embedding-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use spartan8806/echo-tuned-embedding-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("spartan8806/echo-tuned-embedding-v2") 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
File size: 196 Bytes
a67f227 | 1 2 3 4 5 6 7 8 | {
"base_model": "spartan8806/atles-champion-embedding",
"trained_at": "2025-12-07T07:56:19.230529",
"training_examples": 13060,
"epochs": 3,
"batch_size": 16,
"device": "cuda"
} |