Image-to-Text
Transformers
PyTorch
JAX
Portuguese
vision-encoder-decoder
image-text-to-text
image-captioning
Instructions to use adalbertojunior/image_captioning_portuguese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adalbertojunior/image_captioning_portuguese 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="adalbertojunior/image_captioning_portuguese")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("adalbertojunior/image_captioning_portuguese") model = AutoModelForMultimodalLM.from_pretrained("adalbertojunior/image_captioning_portuguese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from adalbertojunior/image_captioning_portuguese: direct link, hf CLI and curl.
- Browser
- Download file 1.46 MB
-
https://huggingface.co/adalbertojunior/image_captioning_portuguese/resolve/main/tokenizer.json
- Command line
-
hf download hf://adalbertojunior/image_captioning_portuguese/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/adalbertojunior/image_captioning_portuguese/resolve/main/tokenizer.json
1.46 MB
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