Instructions to use arampacha/roberta-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arampacha/roberta-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="arampacha/roberta-tiny")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("arampacha/roberta-tiny") model = AutoModelForMaskedLM.from_pretrained("arampacha/roberta-tiny") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7c570ad5c6afb6fec41c8b29d6eb7de50ce14d1bad94f024a2885e80a891a41
- Size of remote file:
- 68.4 MB
- SHA256:
- 5ce6341fedf36b25eacbfde892fd28906f1516b4879659b6f502adabd3b0cfb9
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