Feature Extraction
sentence-transformers
Safetensors
xlm-roberta
sentence-similarity
dense-encoder
dense
retrieval
multimodal
multi-modal
crossmodal
cross-modal
aerospace
telepix
text-embeddings-inference
Instructions to use telepix/PIXIE-Rune-v1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use telepix/PIXIE-Rune-v1.5 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("telepix/PIXIE-Rune-v1.5") 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:
- c35a0a955318dc1fc6472e16c11da4fe538333b46a63bb0d0bf80bbcf6f0a2c7
- Size of remote file:
- 17.1 MB
- SHA256:
- b4909df3b0d2cd3b59a675a60f41fecf38cd5b3ba20975bd77b1e3800995ec2b
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