Instructions to use Elbe/RoBERTaforIns with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Elbe/RoBERTaforIns with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Elbe/RoBERTaforIns")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Elbe/RoBERTaforIns") model = AutoModelForMaskedLM.from_pretrained("Elbe/RoBERTaforIns", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37300476c646543f769a41d1fa7e738e2678dfd6169967ee150b2a43afbae2b6
- Size of remote file:
- 266 MB
- SHA256:
- 90c4599df97e338daa6a24b9439ee4c355c65aae106893c25236ccb5dbac8c52
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