Instructions to use CodeHima/TOSBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CodeHima/TOSBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CodeHima/TOSBert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CodeHima/TOSBert") model = AutoModelForSequenceClassification.from_pretrained("CodeHima/TOSBert") - Notebooks
- Google Colab
- Kaggle
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README.md
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library_name: transformers
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pipeline_tag: text-classification
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metrics:
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- accuracy
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example_title: "Fair Clause"
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- text: " We reserve the right to suspend, terminate, or restrict your access to the platform at any time and for any reason, without prior notice or explanation. This includes but is not limited to violations of our community guidelines or terms of service, as determined solely by ConnectWorld."
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example_title: "Unfair Clause"
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library_name: transformers
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pipeline_tag: text-classification
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tags:
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