Instructions to use LiYuan/amazon-cross-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LiYuan/amazon-cross-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LiYuan/amazon-cross-encoder")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LiYuan/amazon-cross-encoder") model = AutoModelForSequenceClassification.from_pretrained("LiYuan/amazon-cross-encoder") - Notebooks
- Google Colab
- Kaggle
Update model metadata to set pipeline tag to the new `text-ranking` and library name to `sentence-transformers`
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by tomaarsen HF Staff - opened
README.md
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@@ -4,6 +4,8 @@ tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: distilbert-base-uncased-finetuned-mnli
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results: []
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- generated_from_trainer
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metrics:
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- accuracy
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pipeline_tag: text-ranking
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library_name: sentence-transformers
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model-index:
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- name: distilbert-base-uncased-finetuned-mnli
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results: []
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