Text Classification
Transformers
Safetensors
English
distilbert
speech-acts
political-speeches
pragmatics
text-embeddings-inference
Instructions to use syslen/SearleSpeechActBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syslen/SearleSpeechActBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="syslen/SearleSpeechActBert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("syslen/SearleSpeechActBert") model = AutoModelForSequenceClassification.from_pretrained("syslen/SearleSpeechActBert") - Notebooks
- Google Colab
- Kaggle
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Potential use cases include:
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- analysis of political speeches
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- rhetorical analysis
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- annotation assistance
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- corpus exploration
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Potential use cases include:
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- analysis of political speeches
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- annotation assistance
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- corpus exploration
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