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
Download sentence_bert_config.json from spartan8806/echo-tuned-embedding-v2: direct link, hf CLI and curl.
- Browser
- Download file 60 Bytes
-
https://huggingface.co/spartan8806/echo-tuned-embedding-v2/resolve/main/sentence_bert_config.json
- Command line
-
hf download hf://spartan8806/echo-tuned-embedding-v2/sentence_bert_config.json
-
curl -L -o sentence_bert_config.json https://huggingface.co/spartan8806/echo-tuned-embedding-v2/resolve/main/sentence_bert_config.json
60 Bytes
| { | |
| "max_seq_length": 384, | |
| "do_lower_case": false | |
| } |