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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a510ca630b7dda09f11c26119fa2a3b6a3bcef0eaebdb845d4571e4a3a12d415
- Size of remote file:
- 2.23 GB
- SHA256:
- 18bb32c67308c807abeaf53d9239e49b8543143e4b9a7b21ecc615252d652caa
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