Instructions to use Neurona/cpegen_vend with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Neurona/cpegen_vend with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Neurona/cpegen_vend")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Neurona/cpegen_vend") model = AutoModelForTokenClassification.from_pretrained("Neurona/cpegen_vend") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:55cb3f017198176e2040c9a3e85926e55270f4ed16f7ab712896c0e701c42eaa
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size 265473092
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