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:
- 6cc24eec1cf6654d6dbac7dfbfa222ee8e7345975a053e96919330489a41e886
- Size of remote file:
- 346 MB
- SHA256:
- 3135245340940e4b628c505febf8291323c95b225f1a342dcb2d4ea0c8766482
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