Feature Extraction
sentence-transformers
ONNX
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-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use telepix/PIXIE-Rune-v1.0 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("telepix/PIXIE-Rune-v1.0") 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:
- 9b59abff9f481f144030c36b59056d382a09dabecd01a073e5cc303590f3e495
- Size of remote file:
- 17.1 MB
- SHA256:
- 33b81d158d38590c83f2e3b4c3644f5eb63136c14a77f6bdb147913ad33a9bbc
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