Token Classification
Transformers
Safetensors
ONNX
Transformers.js
modernbert
punctuation
punctuation-restoration
asr
speech-recognition
transcription
mmbert
Instructions to use seamon67/Punctuation-Restoration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seamon67/Punctuation-Restoration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="seamon67/Punctuation-Restoration")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("seamon67/Punctuation-Restoration") model = AutoModelForTokenClassification.from_pretrained("seamon67/Punctuation-Restoration", device_map="auto") - Transformers.js
How to use seamon67/Punctuation-Restoration with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('token-classification', 'seamon67/Punctuation-Restoration'); - Notebooks
- Google Colab
- Kaggle
Download eval/baselines.json from seamon67/Punctuation-Restoration: direct link, hf CLI and curl.
- Browser
- Download file 565 kB
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https://huggingface.co/seamon67/Punctuation-Restoration/resolve/main/eval/baselines.json
- Command line
-
hf download hf://seamon67/Punctuation-Restoration/eval/baselines.json
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curl -L -o baselines.json https://huggingface.co/seamon67/Punctuation-Restoration/resolve/main/eval/baselines.json
565 kB
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