Instructions to use Vandy/bartpho-word-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vandy/bartpho-word-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Vandy/bartpho-word-base") model = AutoModelForSeq2SeqLM.from_pretrained("Vandy/bartpho-word-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Vandy/bartpho-word-base: direct link, hf CLI and curl.
- Browser
- Download file 303 Bytes
-
https://huggingface.co/Vandy/bartpho-word-base/resolve/refs%2Fpr%2F1/tokenizer_config.json
- Command line
-
hf download hf://Vandy/bartpho-word-base@refs/pr/1/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Vandy/bartpho-word-base/resolve/refs%2Fpr%2F1/tokenizer_config.json
303 Bytes
| { | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "mask_token": "<mask>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "tokenizer_class": "PhobertTokenizer", | |
| "unk_token": "<unk>" | |
| } | |