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:
- 8298741bf8ed2bd6d3eb93d70c98ed0803e69856fc8ede35f60848e78b66c8d9
- Size of remote file:
- 68.4 MB
- SHA256:
- 6129c5522d8da0b21eb9a6b105c755774789983deca4c333fa180506f304c430
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