Instructions to use SE6446/Untitled7-colab_checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SE6446/Untitled7-colab_checkpoint 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="SE6446/Untitled7-colab_checkpoint")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("SE6446/Untitled7-colab_checkpoint") model = AutoModelForImageTextToText.from_pretrained("SE6446/Untitled7-colab_checkpoint") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4cf8c9fded96e41ef47aa6c6a1903981dac77c01a25135d236954a7b8aa6921f
- Size of remote file:
- 1.58 GB
- SHA256:
- b8579d71c0870032c3c5ee28e7e040d59cc085c312995de8e2eecdc4cf34c0fc
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