Instructions to use moralstories/roberta-large_action-context-consequence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moralstories/roberta-large_action-context-consequence with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="moralstories/roberta-large_action-context-consequence")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("moralstories/roberta-large_action-context-consequence") model = AutoModelForSequenceClassification.from_pretrained("moralstories/roberta-large_action-context-consequence", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 114255eb06f963b1f73c2d394463620888e15120e6f788deee449aa50930ae13
- Size of remote file:
- 1.43 GB
- SHA256:
- 789bd52599281ebb4b71321ce9b45d9301cf87c33ce8264e6c8717f50fbc9a1d
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