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")# 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") - Notebooks
- Google Colab
- Kaggle
Update model metadata to set pipeline tag to the new `text-ranking` and library name to `sentence-transformers`
#2
by tomaarsen HF Staff - opened
README.md
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---
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pipeline_tag: text-
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language:
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-
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datasets:
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- stsb_multi_mt
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tags:
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- cross-encoder
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- sentence-similarity
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- transformers
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---
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# Cross-Encoder
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---
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pipeline_tag: text-ranking
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language:
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- it
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datasets:
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- stsb_multi_mt
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tags:
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- cross-encoder
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- sentence-similarity
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- transformers
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library_name: sentence-transformers
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---
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# Cross-Encoder
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