Instructions to use nlplab/Verdict_Recognizer_Final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlplab/Verdict_Recognizer_Final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="nlplab/Verdict_Recognizer_Final")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("nlplab/Verdict_Recognizer_Final") model = AutoModelForQuestionAnswering.from_pretrained("nlplab/Verdict_Recognizer_Final") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3bb821007e0c538421bce037fbc103df769fb94a2f6d8bfda622c07570295aa
- Size of remote file:
- 39.9 MB
- SHA256:
- 03e61d8b34c21423e3eb77cb32d2f741da851d4478ec580372d23abfaa0f60d7
路
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