Instructions to use Neurona/cpegen_pv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Neurona/cpegen_pv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Neurona/cpegen_pv")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Neurona/cpegen_pv") model = AutoModelForTokenClassification.from_pretrained("Neurona/cpegen_pv") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73bb44ab552cbed5dbde2512673423d2fc13cf991c8a8622d841eceaa79fc676
- Size of remote file:
- 266 MB
- SHA256:
- d366bf25dde49d2a4d6ca3dc3aea6bc1df7d7a7d3c0ef1052703823753143c6d
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