Instructions to use attacker8324/wx293 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use attacker8324/wx293 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="attacker8324/wx293")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("attacker8324/wx293") model = AutoModelForTokenClassification.from_pretrained("attacker8324/wx293", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 346 Bytes
bc9f2fe | 1 | {"do_lower_case": true, "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, "name_or_path": "prajjwal1/bert-tiny", "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "BertTokenizer"} |