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:
- e502067a569d339118b6ee523c9b1fa953991ca0a7b21ee903b99c549b5762e1
- Size of remote file:
- 181 MB
- SHA256:
- f48ca0d25a1bf7745d27ec81351279c48d18767d97215fde7186b64b58a0c442
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