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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Neurona/cpegen_vpv") model = AutoModelForTokenClassification.from_pretrained("Neurona/cpegen_vpv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- config.json +3 -1
- pytorch_model.bin +2 -2
config.json
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"2": "B-vendor",
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"initializer_range": 0.02,
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"max_position_embeddings": 512,
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"initializer_range": 0.02,
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"label2id": {
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"B-version": 3,
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"I-product": 4,
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"I-version": 6,
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"max_position_embeddings": 512,
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pytorch_model.bin
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size 265508386
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