Instructions to use CWrecker/Longformer-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CWrecker/Longformer-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CWrecker/Longformer-Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CWrecker/Longformer-Classification") model = AutoModelForSequenceClassification.from_pretrained("CWrecker/Longformer-Classification") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_prefix_space": false, | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "errors": "replace", | |
| "mask_token": "<mask>", | |
| "model_max_length": 4096, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "tokenizer_class": "LongformerTokenizer", | |
| "trim_offsets": true, | |
| "unk_token": "<unk>" | |
| } | |