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:
- 6782311df215655d2ac93f2d5767723e260550f26b4fd1ba107ad7d715f3b65f
- Size of remote file:
- 4.03 kB
- SHA256:
- 688c9ec825645759d220b540a39b694370fc88eaa986cc24d4a92fb8987a941d
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