Instructions to use ifmain/blip-image2promt-stable-diffusion-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ifmain/blip-image2promt-stable-diffusion-base 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="ifmain/blip-image2promt-stable-diffusion-base")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("ifmain/blip-image2promt-stable-diffusion-base") model = AutoModelForMultimodalLM.from_pretrained("ifmain/blip-image2promt-stable-diffusion-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13ffdcbe374acc291c4066b150fbd6b5ac9c928477d4568077287c83a06df620
- Size of remote file:
- 990 MB
- SHA256:
- 937694134bb1ad3f0a4f259fe01263204a1ec5ac4b27d6b1c517fc484acd6b44
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