Instructions to use Pclanglais/transcript-stances with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pclanglais/transcript-stances with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Pclanglais/transcript-stances")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Pclanglais/transcript-stances") model = AutoModelForSequenceClassification.from_pretrained("Pclanglais/transcript-stances") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33300c8d7cd3b57f17acc729beec2e98dcd5c2333d7f1de969780631e90ddadf
- Size of remote file:
- 1.12 GB
- SHA256:
- 9c3e9457ff6b1677c1ce5283c2ded5a54fb1e8259792fef58d08e0915c10d7d2
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