Text Ranking
sentence-transformers
PyTorch
Safetensors
Transformers
Polish
roberta
text-classification
feature-extraction
sentence-similarity
text-embeddings-inference
Instructions to use radlab/polish-cross-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use radlab/polish-cross-encoder with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("radlab/polish-cross-encoder") query = "Which planet is known as the Red Planet?" passages = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." ] scores = model.predict([(query, passage) for passage in passages]) print(scores) - Transformers
How to use radlab/polish-cross-encoder with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("radlab/polish-cross-encoder") model = AutoModelForSequenceClassification.from_pretrained("radlab/polish-cross-encoder") - Notebooks
- Google Colab
- Kaggle