Token Classification
Transformers
ONNX
Safetensors
Danish
electra
punctuation-restoration
sentence-boundary-detection
truecasing
danish
Instructions to use RyeAI/ekko-pnc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RyeAI/ekko-pnc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="RyeAI/ekko-pnc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("RyeAI/ekko-pnc") model = AutoModelForTokenClassification.from_pretrained("RyeAI/ekko-pnc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Complete PnC model-card metadata
Browse files
README.md
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library_name: transformers
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pipeline_tag: token-classification
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base_model: jonfd/electra-small-nordic
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datasets:
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- alexandrainst/nst-da
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- alexandrainst/ftspeech
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- wikimedia/wikipedia
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tags:
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- punctuation-restoration
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- truecasing
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- danish
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- onnx
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---
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library_name: transformers
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pipeline_tag: token-classification
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base_model: jonfd/electra-small-nordic
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base_model_relation: finetune
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datasets:
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- alexandrainst/nst-da
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- alexandrainst/ftspeech
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- wikimedia/wikipedia
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tags:
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- punctuation-restoration
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- sentence-boundary-detection
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- truecasing
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- danish
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- onnx
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metrics:
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- f1
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---
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