Instructions to use MistahCase/distilroberta-base-testingSB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MistahCase/distilroberta-base-testingSB with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="MistahCase/distilroberta-base-testingSB")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("MistahCase/distilroberta-base-testingSB") model = AutoModelForMaskedLM.from_pretrained("MistahCase/distilroberta-base-testingSB", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 023472c75c01697b7cfc88f003b643007ce25e99a5a4cd4bf311a85a97110f5a
- Size of remote file:
- 329 MB
- SHA256:
- b0510f386204edbd08778723329f82428476f92bf4b92a4c23565370b92966bd
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