Text Classification
Transformers
PyTorch
Italian
bert
cross-encoder
sentence-similarity
text-embeddings-inference
Instructions to use efederici/cross-encoder-bert-base-stsb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use efederici/cross-encoder-bert-base-stsb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="efederici/cross-encoder-bert-base-stsb")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("efederici/cross-encoder-bert-base-stsb") model = AutoModelForSequenceClassification.from_pretrained("efederici/cross-encoder-bert-base-stsb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from efederici/cross-encoder-bert-base-stsb: direct link, hf CLI and curl.
- Browser
- Download file 725 kB
-
https://huggingface.co/efederici/cross-encoder-bert-base-stsb/resolve/refs%2Fpr%2F2/tokenizer.json
- Command line
-
hf download hf://efederici/cross-encoder-bert-base-stsb@refs/pr/2/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/efederici/cross-encoder-bert-base-stsb/resolve/refs%2Fpr%2F2/tokenizer.json
725 kB
File too large to display, you can check the raw version instead.