Instructions to use Joe99/visionlanguageTransformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Joe99/visionlanguageTransformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="Joe99/visionlanguageTransformer")# Load model directly from transformers import AutoProcessor, ViltForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("Joe99/visionlanguageTransformer") model = ViltForVisualQuestionAnswering.from_pretrained("Joe99/visionlanguageTransformer") - Notebooks
- Google Colab
- Kaggle
| {"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, "model_max_length": 40, "special_tokens_map_file": null, "name_or_path": "bert-base-uncased", "tokenizer_class": "BertTokenizer"} |