Instructions to use chrishuber/roberta-kaggledev-testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chrishuber/roberta-kaggledev-testing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="chrishuber/roberta-kaggledev-testing")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("chrishuber/roberta-kaggledev-testing") model = AutoModelForMaskedLM.from_pretrained("chrishuber/roberta-kaggledev-testing", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e90884795eaa7a543dcfc7680614709befdffa0a5f03ecdd621bc1344007a93f
- Size of remote file:
- 499 MB
- SHA256:
- 362c75d14b35f3bdd7828316d1886eaea41310471e707413ab26b131866684e7
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