Instructions to use harish/EN-AStitchTask1A-XLNet-FalseFalse-0-OneShot-0-BEST with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/EN-AStitchTask1A-XLNet-FalseFalse-0-OneShot-0-BEST with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="harish/EN-AStitchTask1A-XLNet-FalseFalse-0-OneShot-0-BEST")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("harish/EN-AStitchTask1A-XLNet-FalseFalse-0-OneShot-0-BEST") model = AutoModelForSequenceClassification.from_pretrained("harish/EN-AStitchTask1A-XLNet-FalseFalse-0-OneShot-0-BEST") - Notebooks
- Google Colab
- Kaggle
| {"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "<sep>", "pad_token": "<pad>", "cls_token": "<cls>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": false}, "additional_special_tokens": ["<eop>", "<eod>"]} |