Instructions to use noamrot/FuseCap_Image_Captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use noamrot/FuseCap_Image_Captioning 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="noamrot/FuseCap_Image_Captioning")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("noamrot/FuseCap_Image_Captioning") model = AutoModelForMultimodalLM.from_pretrained("noamrot/FuseCap_Image_Captioning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
Verified signatureb6793ca
-
Update README.md
4dfafa6
-
Update README.md
e361352
-
Update README.md
5b1dea6 -
Update README.md
de54ab3 -
Update README.md
readme buge977b11 -
Update README.md
added links to github3be0e04
-
Update README.md
c0e9512 -
add python example
6540118 -
cancel inference api
1a4b1f8 -
fixed beam number
b74ad6f
-
fixed all weight names problems
966304f -
small fix
6a5a81b -
fix model weights names
6a946c6 -
added files
e5eee6e -
deleted untrue files
10c3d0d -
add model weights
868b61d -
first actual commit
ba26cb2 -
yaml fix
842136c -
Update README.md
1c54ae2 -
Update README.md
2355c93 -
initial commit
e2f2b2b