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:
- d0a13deab96a470b251b89428bc35a0a62101ec36e9b6d2fbc7be200f6f01d7d
- Size of remote file:
- 3.31 kB
- SHA256:
- fb4e35457707cdf1ed9299019fbe30725065a3e1596609e591b54902bd2064b0
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