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:
- d189ddb9ff53c0be1a2aa6a6d18e9fd88bb2a5cf576e0ce13a8d7bd77d021c95
- Size of remote file:
- 2.8 kB
- SHA256:
- 5a51fec200978334c50c8dd533d4f928bd0392d8d3cdf737d6dbc806ab370a18
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