Instructions to use wikkard/cube0306_fasttokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wikkard/cube0306_fasttokenizer with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("wikkard/cube0306_fasttokenizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download bpe_tokenizer/tokenizer_config.json from wikkard/cube0306_fasttokenizer: direct link, hf CLI and curl.
- Browser
- Download file 314 Bytes
-
https://huggingface.co/wikkard/cube0306_fasttokenizer/resolve/main/bpe_tokenizer/tokenizer_config.json
- Command line
-
hf download hf://wikkard/cube0306_fasttokenizer/bpe_tokenizer/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/wikkard/cube0306_fasttokenizer/resolve/main/bpe_tokenizer/tokenizer_config.json
314 Bytes
| { | |
| "auto_map": { | |
| "AutoProcessor": "processing_action_tokenizer.UniversalActionProcessor" | |
| }, | |
| "backend": "tokenizers", | |
| "clean_up_tokenization_spaces": false, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "processor_class": "UniversalActionProcessor", | |
| "tokenizer_class": "TokenizersBackend" | |
| } | |