Instructions to use Neurona/cpegen_vers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Neurona/cpegen_vers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Neurona/cpegen_vers")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Neurona/cpegen_vers") model = AutoModelForTokenClassification.from_pretrained("Neurona/cpegen_vers", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Neurona/cpegen_vers: direct link, hf CLI and curl.
- Browser
- Download file 265 MB
-
https://huggingface.co/Neurona/cpegen_vers/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Neurona/cpegen_vers/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Neurona/cpegen_vers/resolve/main/pytorch_model.bin
265 MB
- Xet hash:
- d53aeb7a5a48cec3bd52198798b5fb07f0b4061e59d1ec51cacba765ae2ae97e
- Size of remote file:
- 265 MB
- SHA256:
- 6ed7d2131c0b4ef808c53f253b135a519485a959b8a77a9dac477bc315e0438d
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