Instructions to use jeniya/BERTOverflow_stackoverflow_github with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jeniya/BERTOverflow_stackoverflow_github with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jeniya/BERTOverflow_stackoverflow_github")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("jeniya/BERTOverflow_stackoverflow_github") model = AutoModel.from_pretrained("jeniya/BERTOverflow_stackoverflow_github") - Notebooks
- Google Colab
- Kaggle
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## Model description
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We pre-trained BERT-base model on 152 million sentences from the StackOverflow's 10 year archive. More details in our ACL 2020 paper: https://www.aclweb.org/anthology/2020.acl-main.443/. We
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## Model description
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We pre-trained BERT-base model on 152 million sentences from the StackOverflow's 10 year archive. More details of this model can be found in our ACL 2020 paper: [Code and Named Entity Recognition in StackOverflow](https://www.aclweb.org/anthology/2020.acl-main.443/). We would like to thank [Wuwei Lan](https://lanwuwei.github.io/) for helping us in training this model.
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