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")# 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
- Xet hash:
- c6cec2cbf4087f5fdb865cbd8d78f025319dc945869bb8ee50d3767f986eae69
- Size of remote file:
- 896 MB
- SHA256:
- c3f67dee894d52c2d6133f5e147bf5548205b77e80653c324815efcd27625ea6
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