Text Classification
Transformers
PyTorch
Italian
camembert
cross-encoder
sentence-similarity
text-embeddings-inference
Instructions to use efederici/cross-encoder-umberto-stsb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use efederici/cross-encoder-umberto-stsb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="efederici/cross-encoder-umberto-stsb")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("efederici/cross-encoder-umberto-stsb") model = AutoModelForSequenceClassification.from_pretrained("efederici/cross-encoder-umberto-stsb") - Notebooks
- Google Colab
- Kaggle
Update model metadata to set pipeline tag to the new `text-ranking` and library name to `sentence-transformers`
#2 opened about 1 year ago
by
tomaarsen
Adding `safetensors` variant of this model
#1 opened over 1 year ago
by
SFconvertbot