Instructions to use WENGSYX/Multilingual_SimCSE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WENGSYX/Multilingual_SimCSE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="WENGSYX/Multilingual_SimCSE")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("WENGSYX/Multilingual_SimCSE") model = AutoModel.from_pretrained("WENGSYX/Multilingual_SimCSE") - Notebooks
- Google Colab
- Kaggle
| {"do_lower_case": false, "bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "split_by_punct": false, "sp_model_kwargs": {}, "vocab_type": "spm", "special_tokens_map_file": null, "tokenizer_file": null, "name_or_path": "savemodel/240000_0.047472578783811135", "tokenizer_class": "DebertaV2Tokenizer"} |