Instructions to use Taekyoon/test_bert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Taekyoon/test_bert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Taekyoon/test_bert_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Taekyoon/test_bert_model") model = AutoModel.from_pretrained("Taekyoon/test_bert_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Taekyoon/test_bert_model: direct link, hf CLI and curl.
- Browser
- Download file 300 Bytes
-
https://huggingface.co/Taekyoon/test_bert_model/resolve/refs%2Fpr%2F1/tokenizer_config.json
- Command line
-
hf download hf://Taekyoon/test_bert_model@refs/pr/1/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Taekyoon/test_bert_model/resolve/refs%2Fpr%2F1/tokenizer_config.json
300 Bytes
| {"do_lower_case": false, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "BertTokenizer"} |