Instructions to use bertin-project/bertin-base-random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bertin-project/bertin-base-random with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="bertin-project/bertin-base-random")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("bertin-project/bertin-base-random") model = AutoModelForMaskedLM.from_pretrained("bertin-project/bertin-base-random") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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This is a **RoBERTa-base** model trained from scratch in Spanish.
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The training dataset is mc4 (1) subsampling documents to a total of about 50 million examples. Sampling is random.
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This model has been trained for 250.000 steps.
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(1) https://huggingface.co/datasets/bertin-project/mc4-es-sampled
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