Instructions to use DaniilOr/multilingual_framing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DaniilOr/multilingual_framing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DaniilOr/multilingual_framing")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DaniilOr/multilingual_framing") model = AutoModelForSequenceClassification.from_pretrained("DaniilOr/multilingual_framing") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb2de9070b7ee10044f01412875768e281d781d0a0f7565b4403a9012dbd7e5f
- Size of remote file:
- 16.3 MB
- SHA256:
- f15bbc470ab85b034399d5298bd57631cb3042c6795ba84b2fae197be39bbba3
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