Instructions to use MistahCase/distilroberta-base-testingSB-testingSB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MistahCase/distilroberta-base-testingSB-testingSB with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="MistahCase/distilroberta-base-testingSB-testingSB")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("MistahCase/distilroberta-base-testingSB-testingSB") model = AutoModelForMaskedLM.from_pretrained("MistahCase/distilroberta-base-testingSB-testingSB", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4cd943d7b380b513e1d81b2f872398e3262b9a931ab30ba79d2ed69ed46b20d1
- Size of remote file:
- 329 MB
- SHA256:
- 4557a10d80b313691c84346b7506737f5d32034a14417a7a98580f82b073d687
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