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
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5425ae8e98aa78643ea5bc3515f56ad55da1671fd99ddfc57981d9031fb606a0
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size 2446312176
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