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: 389 Bytes
7e2069c | 1 2 3 4 5 6 | EKKO_PNC_MODEL_FILENAME=pnc.onnx
EKKO_PNC_ONNX_SHA256=9ad9fdd3ad4a74666e0da898bf15e209b585215295e9f9080004bfad6147981b
EKKO_PNC_ONNX_DATA_SHA256=9251b238365032e1d1d486c5c8aa9d6f76916df75109f513fbbb0e05cf22af16
EKKO_PNC_TOKENIZER_SHA256=a1e0d43ee307ad7a1ccc23e6e5398d877a68ca7f576067ac507625a0d50e9502
EKKO_PNC_CONFIG_SHA256=dc655c46f69eeb15dd43786ad58fb5862cc794b36cc9d2c426ab5bc4b01f23ca
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