Feature Extraction
sentence-transformers
Safetensors
modernbert
sentence-similarity
sparse-encoder
sparse
splade
telepix
text-embeddings-inference
Instructions to use telepix/PIXIE-Splade-Preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use telepix/PIXIE-Splade-Preview with sentence-transformers:
from sentence_transformers import SparseEncoder model = SparseEncoder("telepix/PIXIE-Splade-Preview") 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 model.safetensors from telepix/PIXIE-Splade-Preview: direct link, hf CLI and curl.
- Browser
- Download file 598 MB
-
https://huggingface.co/telepix/PIXIE-Splade-Preview/resolve/main/model.safetensors
- Command line
-
hf download hf://telepix/PIXIE-Splade-Preview/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/telepix/PIXIE-Splade-Preview/resolve/main/model.safetensors
598 MB
- Xet hash:
- 39ea7dee4951263a841c153c44644209a0706684d35139abb6485954a0eb3d5e
- Size of remote file:
- 598 MB
- SHA256:
- 1869e2c80d885e73805f28977890ad697066463853883524bf7406bcdc5827e6
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