Instructions to use nikchar/claim_detection_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nikchar/claim_detection_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nikchar/claim_detection_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nikchar/claim_detection_bert") model = AutoModelForSequenceClassification.from_pretrained("nikchar/claim_detection_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ad3275994a9ad647ab93e01826cafeba0842c103b09083c02d883f6edfb658e
- Size of remote file:
- 438 MB
- SHA256:
- ad81be12da30ada3c7cf52f56c482653c8627bfcd8ae41da4536a94347680550
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