Feature Extraction
sentence-transformers
ONNX
multilingual
Korean
English
xlm-roberta
sentence-similarity
quantized
dense-encoder
dense
fastembed
text-embeddings-inference
Instructions to use cstr/PIXIE-Rune-v1.0-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use cstr/PIXIE-Rune-v1.0-ONNX with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cstr/PIXIE-Rune-v1.0-ONNX") 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
- Xet hash:
- 93f218052cbd095c2f421b0c933fa9e4cc473e5fab09ba963683c7749e8ae8dc
- Size of remote file:
- 569 MB
- SHA256:
- 27743ac31c8f0b6e2c0a0ba3a09a8a95f2f4f51cdb303081c1fdba3171c4b877
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