Instructions to use fairnlp/bert-dropout with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fairnlp/bert-dropout with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="fairnlp/bert-dropout")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("fairnlp/bert-dropout") model = AutoModel.from_pretrained("fairnlp/bert-dropout", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from fairnlp/bert-dropout: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/fairnlp/bert-dropout/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
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hf download hf://fairnlp/bert-dropout@refs/pr/1/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/fairnlp/bert-dropout/resolve/refs%2Fpr%2F1/tokenizer.json
711 kB
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