Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
Russian
bert
generated-from-trainer
restore_punctuation
Instructions to use markusiko/rubert-base-punctuation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use markusiko/rubert-base-punctuation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="markusiko/rubert-base-punctuation")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("markusiko/rubert-base-punctuation") model = AutoModelForTokenClassification.from_pretrained("markusiko/rubert-base-punctuation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12748298d74e154c8f92c75e29017cc3027d72d15a95f206a387f5860a5fc7a6
- Size of remote file:
- 4.41 kB
- SHA256:
- 0e2e4013bfb19f9b6ddc55cea87f2a38fbb3dcde578e7b43797eccc9cac4268f
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