Instructions to use nkoh01/MSRoberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nkoh01/MSRoberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nkoh01/MSRoberta")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nkoh01/MSRoberta") model = AutoModelForMaskedLM.from_pretrained("nkoh01/MSRoberta") - Notebooks
- Google Colab
- Kaggle
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Fine-tuned RoBERTa MLM model for [`Miscrosoft Sentence Completion Challenge`](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/MSR_SCCD.pdf). This model case-sensitive following the `Roberta-base` model.
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# Model description (taken from
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RoBERTa is a transformers model pretrained on a large corpus of English data in a self-supervised fashion. This means
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it was pretrained on the raw texts only, with no humans labelling them in any way (which is why it can use lots of
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Fine-tuned RoBERTa MLM model for [`Miscrosoft Sentence Completion Challenge`](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/MSR_SCCD.pdf). This model case-sensitive following the `Roberta-base` model.
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# Model description (taken from: [here](https://huggingface.co/roberta-base))
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RoBERTa is a transformers model pretrained on a large corpus of English data in a self-supervised fashion. This means
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it was pretrained on the raw texts only, with no humans labelling them in any way (which is why it can use lots of
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