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
Create README.md
Browse files
README.md
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**transcript-stances** is an encoder model specialized for the classification of French news transcripts. The model is based on debertav3 and has been trained on 116,000 examples of annotated transcripts.
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Given a text, transcript-text-analysis will generate the following classifications in French:
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* Positive stance
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* Neutral stance
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* Negative stance
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* Sarcasm index
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