Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
Safetensors
Transformers
Polish
roberta
feature-extraction
text-embeddings-inference
Instructions to use sdadas/st-polish-paraphrase-from-distilroberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sdadas/st-polish-paraphrase-from-distilroberta with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sdadas/st-polish-paraphrase-from-distilroberta") 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] - Transformers
How to use sdadas/st-polish-paraphrase-from-distilroberta with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sdadas/st-polish-paraphrase-from-distilroberta") model = AutoModel.from_pretrained("sdadas/st-polish-paraphrase-from-distilroberta") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3711c8d35378cfffbdfccb635ded04c63dbe9c6386c7bb63d6be4032a0f490a
- Size of remote file:
- 498 MB
- SHA256:
- e02fb1ba9e281f4bc774029f5a03bbc0c690e6250f00eeecc230fa098b2c9c0b
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