Instructions to use firqaaa/indo-dpr-question_encoder-multiset-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use firqaaa/indo-dpr-question_encoder-multiset-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="firqaaa/indo-dpr-question_encoder-multiset-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("firqaaa/indo-dpr-question_encoder-multiset-base") model = AutoModel.from_pretrained("firqaaa/indo-dpr-question_encoder-multiset-base") - Notebooks
- Google Colab
- Kaggle
| { | |
| "cls_token": "[CLS]", | |
| "do_basic_tokenize": true, | |
| "do_lower_case": true, | |
| "full_tokenizer_file": null, | |
| "mask_token": "[MASK]", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "name_or_path": "cahya/bert-base-indonesian-1.5G", | |
| "never_split": null, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "special_tokens_map_file": null, | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "DPRQuestionEncoderTokenizer", | |
| "unk_token": "[UNK]", | |
| "use_fast": true | |
| } | |