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")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tifa-benchmark/promptcap-coco-vqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
de7d203
-
Update README.md
4101b50
-
Update README.md
44aa161
-
Update README.md
a5c6185
-
Update README.md
00fd1b8
-
Update README.md
7847f46 -
Update README.md
a094e0c -
Update README.md
5eb3f77 -
Update README.md
7cef707 -
Update README.md
f1e34bc -
Update README.md
cb72bec -
Update README.md
68336b4
-
Update README.md
502c77d -
Update README.md
5d845fe -
Update README.md
b4cf00d
-
initial commit
9b1371d -
initial commit
b027fb0