Instructions to use christinacdl/clickbait_binary_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use christinacdl/clickbait_binary_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="christinacdl/clickbait_binary_detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("christinacdl/clickbait_binary_detection") model = AutoModelForSequenceClassification.from_pretrained("christinacdl/clickbait_binary_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:22e1189237e1c296060d36725834c1ac7e403783949251c719fb6a523e6561d2
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size 1421499616
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