Sentence Similarity
sentence-transformers
TensorBoard
Safetensors
bert
feature-extraction
Trained with AutoTrain
text-embeddings-inference
Instructions to use PyxiLab/Pyx-embeds with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use PyxiLab/Pyx-embeds with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("PyxiLab/Pyx-embeds") sentences = [ "search_query: i love autotrain", "search_query: huggingface auto train", "search_query: hugging face auto train", "search_query: i love autotrain" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54f7984ea7b4247cfe26cfaaf7e3c7114f7c0f65082da3cf459fc23923a3ffb5
- Size of remote file:
- 5.62 kB
- SHA256:
- aa0cc08b7eb4aa3a6ca19aa5a7763e86ccb5a8551fc2bc4d5c7e0e6ef2d74224
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