Instructions to use Neurona/cpegen_vpv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Neurona/cpegen_vpv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Neurona/cpegen_vpv")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Neurona/cpegen_vpv") model = AutoModelForTokenClassification.from_pretrained("Neurona/cpegen_vpv") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5598fbdbcb80c27fad08509672eb17af6db74d4f78f8dc2555208d1c8255e49a
- Size of remote file:
- 266 MB
- SHA256:
- 789b6d82ef0bb40205f9629fc50f91aa3371de2f2f37590b54d378bd48cf4f1c
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