Image-to-Text
Transformers
Safetensors
English
vision-encoder-decoder
image-text-to-text
vit
bert
vision
caption
captioning
image
Instructions to use cnmoro/tiny-image-captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cnmoro/tiny-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="cnmoro/tiny-image-captioning")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("cnmoro/tiny-image-captioning") model = AutoModelForImageTextToText.from_pretrained("cnmoro/tiny-image-captioning") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1122988ee4e848856b19f3955389bf079f5f2d14384fdb39b255baf8faf81509
- Size of remote file:
- 106 MB
- SHA256:
- cb2ef6ae2991a81f88e295a59ead95715780045e1f465e68ffe1c5b9ba91ae6a
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