Feature Extraction
sentence-transformers
Safetensors
xlm-roberta
sentence-similarity
dense-encoder
dense
telepix
text-embeddings-inference
Instructions to use telepix/PIXIE-Rune-Preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use telepix/PIXIE-Rune-Preview with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("telepix/PIXIE-Rune-Preview") 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
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README.md
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from sentence_transformers import SentenceTransformer
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# Load the model
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model_name = 'PIXIE-Rune-
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model = SentenceTransformer(model_name)
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# Define the queries and documents
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from sentence_transformers import SentenceTransformer
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# Load the model
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model_name = 'telepix/PIXIE-Rune-Preview'
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model = SentenceTransformer(model_name)
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# Define the queries and documents
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