Instructions to use NbAiLab/roberta_jan_128_ncc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/roberta_jan_128_ncc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLab/roberta_jan_128_ncc")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLab/roberta_jan_128_ncc") model = AutoModelForMaskedLM.from_pretrained("NbAiLab/roberta_jan_128_ncc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ee53138ee7a7f47b47dd7b48c0c257de4831dae1979ce05d9cc1541ccc1650d
- Size of remote file:
- 499 MB
- SHA256:
- 4abb41156cf5e1bcf659c487aa968be2612b5af34c29a3e312dedf77fe42746c
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