Instructions to use jkruk/distilroberta-base-ft-consoom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jkruk/distilroberta-base-ft-consoom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jkruk/distilroberta-base-ft-consoom")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jkruk/distilroberta-base-ft-consoom") model = AutoModelForMaskedLM.from_pretrained("jkruk/distilroberta-base-ft-consoom") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fdc031c7bac365122e6f583a634d3c09a060aeccdff01a88951f209e6bef8587
- Size of remote file:
- 329 MB
- SHA256:
- bad73a827cea1e098f55c7c7bc2bbd1d652798bdd674e15417da9f96d6482a8f
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