Feature Extraction
sentence-transformers
Safetensors
topk_embed
image-text-to-text
multi-vector
retrieval
custom_code
late-interaction
Instructions to use topk-io/topk-embed-v1-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use topk-io/topk-embed-v1-small with sentence-transformers:
from sentence_transformers import MultiVectorEncoder model = MultiVectorEncoder("topk-io/topk-embed-v1-small", trust_remote_code=True) queries = ["Which planet is known as the Red Planet?"] documents = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", ] query_embeddings = model.encode_query(queries) document_embeddings = model.encode_document(documents) similarities = model.similarity(query_embeddings, document_embeddings) print(similarities) - Notebooks
- Google Colab
- Kaggle
Download pooling-recall.png from topk-io/topk-embed-v1-small: direct link, hf CLI and curl.
- Browser
- Download file 147 kB
-
https://huggingface.co/topk-io/topk-embed-v1-small/resolve/main/pooling-recall.png
- Command line
-
hf download hf://topk-io/topk-embed-v1-small/pooling-recall.png
-
curl -L -o pooling-recall.png https://huggingface.co/topk-io/topk-embed-v1-small/resolve/main/pooling-recall.png
147 kB

- Xet hash:
- 32e23557b6726415700e1dd333ae44af5350b0c714036a50f7e1943bc99cc84d
- Size of remote file:
- 147 kB
- SHA256:
- 3e9a5c4abd5d1c9cf02df92f482346de54f9ce06e5e533638c505a0b5a180a27
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.