Instructions to use deepakachu/rsicd_image_captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepakachu/rsicd_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="deepakachu/rsicd_image_captioning")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("deepakachu/rsicd_image_captioning") model = AutoModelForImageTextToText.from_pretrained("deepakachu/rsicd_image_captioning") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 094f682037d58858cdfeddf870a813bc9941c1240556f44441762dc1b9ecd89e
- Size of remote file:
- 707 MB
- SHA256:
- b4c0e368702aee05e71dfae921cfd6fe018320546b4420814598d4384c61e862
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