Instructions to use nlpaueb/sec-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpaueb/sec-bert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nlpaueb/sec-bert-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("nlpaueb/sec-bert-base") model = AutoModelForPreTraining.from_pretrained("nlpaueb/sec-bert-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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README.md
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model = AutoModel.from_pretrained("nlpaueb/sec-bert-base")
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## Use
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| Sample | Masked Token |
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model = AutoModel.from_pretrained("nlpaueb/sec-bert-base")
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```
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## Use SEC-BERT variants as Language Models
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| Sample | Masked Token |
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| --------------------------------------------------- | ------------ |
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