Instructions to use pstroe/roberta-base-latin-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pstroe/roberta-base-latin-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="pstroe/roberta-base-latin-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("pstroe/roberta-base-latin-cased") model = AutoModelForMaskedLM.from_pretrained("pstroe/roberta-base-latin-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74bfabb908b4667e00f9d6785b28abc289014f904d66162d65eacec927218caa
- Size of remote file:
- 499 MB
- SHA256:
- 5f0726e20d11e9240317ed04d26d229c3f67b699605ca33c7d85e50a7095c380
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