Instructions to use anhuu/argument_classification_stance_topictext_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anhuu/argument_classification_stance_topictext_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anhuu/argument_classification_stance_topictext_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anhuu/argument_classification_stance_topictext_bert") model = AutoModelForSequenceClassification.from_pretrained("anhuu/argument_classification_stance_topictext_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 59cd18e166c6ce651e154d30844ddec27eaea384293ce62093ab8f7374faf189
- Size of remote file:
- 438 MB
- SHA256:
- 581b78444b6b72131497f2f7412c85e2592d4e454a394c5f488c7c0e91d5394a
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