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 flax_model.msgpack from adalbertojunior/image_captioning_portuguese: direct link, hf CLI and curl.
- Browser
- Download file 957 MB
-
https://huggingface.co/adalbertojunior/image_captioning_portuguese/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://adalbertojunior/image_captioning_portuguese/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/adalbertojunior/image_captioning_portuguese/resolve/main/flax_model.msgpack
957 MB
- Xet hash:
- 3954ea9506274e8dcbed83a7ebc1e3d7c4c9172046f09d010ec8e9de47f3220d
- Size of remote file:
- 957 MB
- SHA256:
- d7c9124fe3adaf62e207f6c751659842b56f762770e898af36f5e8b3667614e9
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