Instructions to use anmol-unitmole/longformer-qasper-document-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anmol-unitmole/longformer-qasper-document-qa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="anmol-unitmole/longformer-qasper-document-qa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("anmol-unitmole/longformer-qasper-document-qa") model = AutoModelForQuestionAnswering.from_pretrained("anmol-unitmole/longformer-qasper-document-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "errors": "replace", | |
| "is_local": true, | |
| "local_files_only": false, | |
| "mask_token": "<mask>", | |
| "max_length": 3072, | |
| "model_max_length": 4096, | |
| "pad_to_multiple_of": null, | |
| "pad_token": "<pad>", | |
| "pad_token_type_id": 0, | |
| "padding_side": "right", | |
| "sep_token": "</s>", | |
| "stride": 384, | |
| "tokenizer_class": "RobertaTokenizer", | |
| "trim_offsets": true, | |
| "truncation_side": "right", | |
| "truncation_strategy": "only_second", | |
| "unk_token": "<unk>" | |
| } | |