Instructions to use JackBAI/roberta-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JackBAI/roberta-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="JackBAI/roberta-medium")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("JackBAI/roberta-medium") model = AutoModelForMaskedLM.from_pretrained("JackBAI/roberta-medium") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -43,7 +43,7 @@ Evaluation Scores Curve (AVG of scores) during pretraining:
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For both stats above we don't report CoLA scores as it's pretty unstable. The raw CoLA scores are:
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CoLA | 1.7 | 13.5 | 29.2 | 31.4 | 31.1 | 24.1 | 29.0 | 20.0 |
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For both stats above we don't report CoLA scores as it's pretty unstable. The raw CoLA scores are:
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| Step | 1500 | 3000 | 6000 | 9000 | 13500 | 18000 | 24000 | 30000 |
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CoLA | 1.7 | 13.5 | 29.2 | 31.4 | 31.1 | 24.1 | 29.0 | 20.0 |
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