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
File size: 417 Bytes
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"boundary_logit_bias": 0.75,
"applied_to_label_ids": [
4,
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9
],
"applied_to_labels": [
".",
".|U",
"?",
"?|U",
"!",
"!|U"
],
"classifier_bias_delta": [
0.0,
0.0,
0.0,
0.0,
0.75,
0.75,
0.75,
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],
"selected_on": "CoRal conversation running-text DEV (random cuts), not on any test set"
}
|