Instructions to use Seungjun/image_captioner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Seungjun/image_captioner 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="Seungjun/image_captioner")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Seungjun/image_captioner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e47ef36c560e6afb9565a2219ab51104a71c5d026a65cc42e8368e3ecda301ab
- Size of remote file:
- 177 MB
- SHA256:
- 27d6078fc6d17e4489346ebc9fa8709d22d1e98a42b3cfde5e08d023e3c24ca6
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