Instructions to use Caraaaaa/text_image_captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Caraaaaa/text_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="Caraaaaa/text_image_captioning")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Caraaaaa/text_image_captioning") model = AutoModelForMultimodalLM.from_pretrained("Caraaaaa/text_image_captioning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Caraaaaa/text_image_captioning: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/Caraaaaa/text_image_captioning/resolve/00a22ae2f4e5cfeedb8b0882ba49b3e4eb3eb8c3/tokenizer.json
- Command line
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hf download hf://Caraaaaa/text_image_captioning@00a22ae2f4e5cfeedb8b0882ba49b3e4eb3eb8c3/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Caraaaaa/text_image_captioning/resolve/00a22ae2f4e5cfeedb8b0882ba49b3e4eb3eb8c3/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.