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", device_map="auto")# 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:
- d97287f1a3d6072769a88e1a29c723efa2d669f03d41d46d579ebe99ba897d61
- Size of remote file:
- 499 MB
- SHA256:
- 368cc3c8683964246fb12bb8fc3d732615061dc113dfc4c581f79860732c12a0
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