Instructions to use kd13/RoPERT-MLM-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kd13/RoPERT-MLM-mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="kd13/RoPERT-MLM-mini", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("kd13/RoPERT-MLM-mini", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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Masked Language Modelling (MLM) with a masking probability of **30 %**. The standard 80/10/10 mask/replace/keep strategy is applied by `DataCollatorForLanguageModeling`.
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## Usage
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Masked Language Modelling (MLM) with a masking probability of **30 %**. The standard 80/10/10 mask/replace/keep strategy is applied by `DataCollatorForLanguageModeling`.
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## Evalution Details
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Perplexity : 12.59
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## Usage
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