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
Upload onnx/model_quantized.onnx with huggingface_hub
Browse files
onnx/model_quantized.onnx
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