Sentence Similarity
sentence-transformers
PyTorch
Safetensors
Transformers
Polish
roberta
feature-extraction
text-embeddings-inference
Instructions to use radlab/polish-bi-encoder-mean with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use radlab/polish-bi-encoder-mean with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("radlab/polish-bi-encoder-mean") 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 radlab/polish-bi-encoder-mean with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("radlab/polish-bi-encoder-mean") model = AutoModel.from_pretrained("radlab/polish-bi-encoder-mean") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1ccf2276e6749d1d4a93c26ed00f711114a28805e6f3d3b38e09775dd6a5636
- Size of remote file:
- 1.74 GB
- SHA256:
- 701a73f8aa0605d962b6f59e7dccb8c1879d18bf3a6561830f090c6b1b24cedc
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