Token Classification
Transformers
Safetensors
Finnish
electra
punctuation-restoration
sentence-boundary-detection
truecasing
speech-recognition
streaming
finnish
Instructions to use samuli/mateli-punct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use samuli/mateli-punct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="samuli/mateli-punct")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("samuli/mateli-punct") model = AutoModelForTokenClassification.from_pretrained("samuli/mateli-punct", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 586 Bytes
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"tokenizer_class": "PreTrainedTokenizerFast",
"cls_token": "[CLS]",
"sep_token": "[SEP]",
"pad_token": "[PAD]",
"unk_token": "[UNK]",
"mask_token": "[MASK]",
"additional_special_tokens": [
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],
"model_max_length": 512
} |