Instructions to use karoldobiczek/roberta-base_fomc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karoldobiczek/roberta-base_fomc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karoldobiczek/roberta-base_fomc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karoldobiczek/roberta-base_fomc") model = AutoModelForSequenceClassification.from_pretrained("karoldobiczek/roberta-base_fomc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a0ff9c4f249938f056a69403bdde11f105a0ade004fd0584d0dad32658c291d
- Size of remote file:
- 499 MB
- SHA256:
- 852d5f2fde2a3cb2477d0a5d4fbbc6a12e4e89740fa5345edd3bd0ac1e6059a2
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