Instructions to use anhuu/argument_classification_stance_topictexttarget_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anhuu/argument_classification_stance_topictexttarget_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anhuu/argument_classification_stance_topictexttarget_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anhuu/argument_classification_stance_topictexttarget_bert") model = AutoModelForSequenceClassification.from_pretrained("anhuu/argument_classification_stance_topictexttarget_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 348e409887c5ea737d2a3d30e043b1e4dc21b47a791adc1e80de8112c318afb0
- Size of remote file:
- 4.47 kB
- SHA256:
- af5bc7b24e1ecf766ceb3bb8d06dc2272b7a8d073fd9adb5c6d24c6b4af9e903
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