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
File size: 227 Bytes
733254c | 1 2 3 4 5 6 | epoch,steps,Pearson_Correlation,Spearman_Correlation
0,-1,0.855315241536417,0.8491118727278618
1,-1,0.8676937353054238,0.8639392227916658
2,-1,0.8759491508537594,0.871237024968008
3,-1,0.874309299933148,0.8691823634113681
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