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:
- 0bd0989dd48362726558d24a0f2622fb192acf3516286e167f1aa19fb7e3e295
- Size of remote file:
- 3.71 kB
- SHA256:
- d487a0551bf854cb27a772e9ce52d646b909425f98f558366697870f2581839e
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