Instructions to use filevich/robertita-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use filevich/robertita-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="filevich/robertita-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("filevich/robertita-cased") model = AutoModelForMaskedLM.from_pretrained("filevich/robertita-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 751de742f921123107e9038d69ffa338998014d873ba2e4912a9f85cc7c5f57d
- Size of remote file:
- 877 MB
- SHA256:
- 2c344206802676a4c1c6c7ed3dc503a63517a79aaf7a9a4ab8690235fa7cb732
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