Instructions to use tiennvcs/bert-base-uncased-finetuned-infovqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiennvcs/bert-base-uncased-finetuned-infovqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="tiennvcs/bert-base-uncased-finetuned-infovqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("tiennvcs/bert-base-uncased-finetuned-infovqa") model = AutoModelForQuestionAnswering.from_pretrained("tiennvcs/bert-base-uncased-finetuned-infovqa") - Notebooks
- Google Colab
- Kaggle
File size: 112 Bytes
cf6ab4e | 1 | {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"} |