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
Download tokenizer_config.json from samuli/mateli-punct: direct link, hf CLI and curl.
- Browser
- Download file 586 Bytes
-
https://huggingface.co/samuli/mateli-punct/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://samuli/mateli-punct/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/samuli/mateli-punct/resolve/main/tokenizer_config.json
586 Bytes
| { | |
| "tokenizer_class": "PreTrainedTokenizerFast", | |
| "cls_token": "[CLS]", | |
| "sep_token": "[SEP]", | |
| "pad_token": "[PAD]", | |
| "unk_token": "[UNK]", | |
| "mask_token": "[MASK]", | |
| "additional_special_tokens": [ | |
| "[unused0]", | |
| "[unused1]", | |
| "[unused2]", | |
| "[unused3]", | |
| "[unused4]", | |
| "[unused5]", | |
| "[unused6]", | |
| "[unused7]", | |
| "[unused8]", | |
| "[unused9]", | |
| "[unused10]", | |
| "[unused11]", | |
| "[unused12]", | |
| "[unused13]", | |
| "[unused14]", | |
| "[unused15]", | |
| "[unused16]", | |
| "[unused17]", | |
| "[unused18]", | |
| "[unused19]" | |
| ], | |
| "model_max_length": 512 | |
| } |