Instructions to use Salesforce/blip-vqa-capfilt-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Salesforce/blip-vqa-capfilt-large with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "visual-question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("visual-question-answering", model="Salesforce/blip-vqa-capfilt-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("Salesforce/blip-vqa-capfilt-large") model = AutoModelForVisualQuestionAnswering.from_pretrained("Salesforce/blip-vqa-capfilt-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from Salesforce/blip-vqa-capfilt-large: direct link, hf CLI and curl.
- Browser
- Download file 125 Bytes
-
https://huggingface.co/Salesforce/blip-vqa-capfilt-large/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://Salesforce/blip-vqa-capfilt-large/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/Salesforce/blip-vqa-capfilt-large/resolve/main/special_tokens_map.json
125 Bytes
| { | |
| "cls_token": "[CLS]", | |
| "mask_token": "[MASK]", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "unk_token": "[UNK]" | |
| } | |