Instructions to use nnpy/blip-image-captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nnpy/blip-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="nnpy/blip-image-captioning")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("nnpy/blip-image-captioning") model = AutoModelForImageTextToText.from_pretrained("nnpy/blip-image-captioning") - Notebooks
- Google Colab
- Kaggle
Commit ·
b413986
1
Parent(s): 9e192f4
Adding `safetensors` variant of this model (#4)
Browse files- Adding `safetensors` variant of this model (4552b8fd432bd0de23fd2b9054faf00ba5f90952)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:e84832b8a5f3ecad2b0ffede0e41ed609e4c0d75cdbb92d62be140cefb108814
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size 989721256
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