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 pytorch_model.bin from efederici/cross-encoder-bert-base-stsb: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/efederici/cross-encoder-bert-base-stsb/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://efederici/cross-encoder-bert-base-stsb/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/efederici/cross-encoder-bert-base-stsb/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- 3298bd08b27b6abe403a722bd10a2b283b1b3f86d6eaa85478f77bd09b699e75
- Size of remote file:
- 443 MB
- SHA256:
- f4493d4648d77e40aadc1ee7c191dcb0df62fd411f4359db7282ee9804ec1963
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