Instructions to use junnyu/structbert-large-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junnyu/structbert-large-zh with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="junnyu/structbert-large-zh")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("junnyu/structbert-large-zh") model = AutoModel.from_pretrained("junnyu/structbert-large-zh", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 435 Bytes
512e25c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"do_lower_case": true,
"do_basic_tokenize": true,
"never_split": null,
"unk_token": "[UNK]",
"sep_token": "[SEP]",
"pad_token": "[PAD]",
"cls_token": "[CLS]",
"mask_token": "[MASK]",
"tokenize_chinese_chars": true,
"strip_accents": null,
"special_tokens_map_file": null,
"tokenizer_file": null,
"name_or_path": "junnyu/structbert-large-zh",
"tokenizer_class": "BertTokenizer"
} |