Instructions to use sudy-super/Sentinel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sudy-super/Sentinel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sudy-super/Sentinel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sudy-super/Sentinel") model = AutoModelForSequenceClassification.from_pretrained("sudy-super/Sentinel") - Notebooks
- Google Colab
- Kaggle
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Parent(s): 714c822
Update README.md
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README.md
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import torch
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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tokenizer = AutoTokenizer.from_pretrained("sudy-super/
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model = AutoModelForSequenceClassification.from_pretrained("sudy-super/
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def pred(text):
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tokenized_text = tokenizer.tokenize(text)
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import torch
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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tokenizer = AutoTokenizer.from_pretrained("sudy-super/Sentinel")
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model = AutoModelForSequenceClassification.from_pretrained("sudy-super/Sentinel")
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def pred(text):
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tokenized_text = tokenizer.tokenize(text)
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