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:
- 09638d28c054c77ceb39f9e0ebba54287d7aa233a40099a44153f1fe8a09d56c
- Size of remote file:
- 438 MB
- SHA256:
- fe47b51a4d14aa9a71affc1d7b42e1127bbaa2652717839f16f496165528a203
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