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:
- 71e01b35ed85b9fabc107b7ca6139c6cdf6fd1871c8344531604a6e4b44183b7
- Size of remote file:
- 4.47 kB
- SHA256:
- 0e176036c6679f2725dfbdfa06f8514d1090c5981d2dccdb91fadc6a463033ee
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