Sentence Similarity
sentence-transformers
ONNX
Safetensors
OpenVINO
static-embedding
embeddings
feature-extraction
matryoshka
retrieval
Instructions to use hotchpotch/bekko-static-embedding-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use hotchpotch/bekko-static-embedding-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("hotchpotch/bekko-static-embedding-v1") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Download modules.json from hotchpotch/bekko-static-embedding-v1: direct link, hf CLI and curl.
- Browser
- Download file 156 Bytes
-
https://huggingface.co/hotchpotch/bekko-static-embedding-v1/resolve/main/modules.json
- Command line
-
hf download hf://hotchpotch/bekko-static-embedding-v1/modules.json
-
curl -L -o modules.json https://huggingface.co/hotchpotch/bekko-static-embedding-v1/resolve/main/modules.json
156 Bytes
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.sentence_transformer.modules.static_embedding.StaticEmbedding" | |
| } | |
| ] |