Instructions to use Tippawan/wangchanberta-thai-ambiguous-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tippawan/wangchanberta-thai-ambiguous-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tippawan/wangchanberta-thai-ambiguous-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tippawan/wangchanberta-thai-ambiguous-sentiment") model = AutoModelForSequenceClassification.from_pretrained("Tippawan/wangchanberta-thai-ambiguous-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_prefix_space": true, | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "extra_special_tokens": [ | |
| "<s>NOTUSED", | |
| "</s>NOTUSED", | |
| "<_>" | |
| ], | |
| "is_local": false, | |
| "local_files_only": false, | |
| "mask_token": "<mask>", | |
| "max_length": 510, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "sp_model_kwargs": {}, | |
| "stride": 0, | |
| "tokenizer_class": "CamembertTokenizer", | |
| "truncation_side": "right", | |
| "truncation_strategy": "longest_first", | |
| "unk_token": "<unk>" | |
| } | |