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
File size: 232 Bytes
f027ec8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"__version__": {
"sentence_transformers": "4.0.1",
"transformers": "4.51.3",
"pytorch": "2.6.0+cu124"
},
"prompts": {
"query": "query: "
},
"default_prompt_name": null,
"similarity_fn_name": "cosine"
}
|