Feature Extraction
Transformers
Safetensors
PyTorch
Russian
accentik
russian
accentuation
word-stress
custom-code
custom_code
Instructions to use TeraSpace/accentik with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TeraSpace/accentik with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="TeraSpace/accentik", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TeraSpace/accentik", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from TeraSpace/accentik: direct link, hf CLI and curl.
- Browser
- Download file 377 Bytes
-
https://huggingface.co/TeraSpace/accentik/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://TeraSpace/accentik/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/TeraSpace/accentik/resolve/main/tokenizer_config.json
377 Bytes
| { | |
| "backend": "tokenizers", | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "is_local": true, | |
| "local_files_only": true, | |
| "mask_token": "[MASK]", | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 512, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": "[UNK]" | |
| } | |