Instructions to use Bugpie/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bugpie/dummy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Bugpie/dummy-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Bugpie/dummy-model") model = AutoModelForMaskedLM.from_pretrained("Bugpie/dummy-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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## Training data
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OSCAR or Open Super-large Crawled Aggregated coRpus is a multilingual corpus obtained by language classification and filtering of the Common Crawl corpus using the Ungoliant architecture.
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## Training procedure
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## Evaluation results
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## Training data
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OSCAR or Open Super-large Crawled Aggregated coRpus is a multilingual corpus obtained by language classification and filtering of the Common Crawl corpus using the Ungoliant architecture.
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