Instructions to use intanm/clickbaitspoiling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use intanm/clickbaitspoiling with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("bert-base-multilingual-cased") model.load_adapter("intanm/clickbaitspoiling", set_active=True) - Notebooks
- Google Colab
- Kaggle
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Download README.md from intanm/clickbaitspoiling: direct link, hf CLI and curl.
- Browser
- Download file 1.23 kB
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https://huggingface.co/intanm/clickbaitspoiling/resolve/main/README.md
- Command line
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hf download hf://intanm/clickbaitspoiling/README.md
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curl -L -o README.md https://huggingface.co/intanm/clickbaitspoiling/resolve/main/README.md
1.23 kB
metadata
tags:
- adapter-transformers
- bert
- adapterhub:clickbait-spoiling/webis
datasets:
- webis-clickbait-spoiling
Adapter intanm/clickbaitspoiling for bert-base-multilingual-cased
An adapter for the bert-base-multilingual-cased model that was trained on the clickbait-spoiling/webis dataset.
This adapter was created for usage with the adapter-transformers library.
Usage
First, install adapter-transformers:
pip install -U adapter-transformers
Note: adapter-transformers is a fork of transformers that acts as a drop-in replacement with adapter support. More
Now, the adapter can be loaded and activated like this:
from transformers import AutoAdapterModel
model = AutoAdapterModel.from_pretrained("bert-base-multilingual-cased")
adapter_name = model.load_adapter("intanm/clickbaitspoiling", source="hf", set_active=True)