Instructions to use VCNC/Auto-CNC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VCNC/Auto-CNC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VCNC/Auto-CNC")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VCNC/Auto-CNC") model = AutoModelForSequenceClassification.from_pretrained("VCNC/Auto-CNC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c8fffe1caf0510f948cb0f73183b1f208f846bc2f2ef7cf8de2f1899dbbd058
- Size of remote file:
- 9.21 MB
- SHA256:
- 13c824fde60a9982a7f27815519c56bae6f4bf5c19f56b3188ec846d86926be3
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