Instructions to use tifa-benchmark/promptcap-coco-vqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tifa-benchmark/promptcap-coco-vqa with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" 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("image-to-text", model="tifa-benchmark/promptcap-coco-vqa")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tifa-benchmark/promptcap-coco-vqa", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22e9da6311a3a5bbfc751b130dba279e01d9f20c724f081905120b5c02212581
- Size of remote file:
- 2.45 GB
- SHA256:
- bc129c57a1e2645970310f7dbd830fc3f873803d414d375ad25a813842b4059b
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