Image-to-Text
Transformers
PyTorch
Chinese
vision-encoder-decoder
image-text-to-text
image-captioning
Instructions to use Maciel/Muge-Image-Caption with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maciel/Muge-Image-Caption 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="Maciel/Muge-Image-Caption")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("Maciel/Muge-Image-Caption") model = AutoModelForImageTextToText.from_pretrained("Maciel/Muge-Image-Caption") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:622c5d0d7ce5d3f13f17280958f71dd6c280672de32f896765caff742f78aacc
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size 1860706728
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