Sentence Similarity
sentence-transformers
PyTorch
Safetensors
Transformers
Polish
roberta
feature-extraction
text-embeddings-inference
Instructions to use sdadas/st-polish-paraphrase-from-mpnet 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-mpnet with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sdadas/st-polish-paraphrase-from-mpnet") 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-mpnet with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sdadas/st-polish-paraphrase-from-mpnet") model = AutoModel.from_pretrained("sdadas/st-polish-paraphrase-from-mpnet", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download model.safetensors from sdadas/st-polish-paraphrase-from-mpnet: direct link, hf CLI and curl.
- Browser
- Download file 498 MB
-
https://huggingface.co/sdadas/st-polish-paraphrase-from-mpnet/resolve/main/model.safetensors
- Command line
-
hf download hf://sdadas/st-polish-paraphrase-from-mpnet/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/sdadas/st-polish-paraphrase-from-mpnet/resolve/main/model.safetensors
498 MB
- Xet hash:
- ee6ca65294e98af9f691862380813075db67d1024520a96d4356d2019989fc12
- Size of remote file:
- 498 MB
- SHA256:
- dc4aba25f26441c4a774b7ae869f945473d49f972cf3f1d22c4c5732be706de8
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