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:
- 078f5feb806c5f73320db28057792651777ed40493f3ecb54fb934d5501d09d7
- Size of remote file:
- 2.27 GB
- SHA256:
- 3913f9c30fc83ad6e2ea48e339531aaf3fae4144547ce54dcc77aece3d9ba290
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