Instructions to use nlpconnect/vit-gpt2-image-captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpconnect/vit-gpt2-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="nlpconnect/vit-gpt2-image-captioning")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("nlpconnect/vit-gpt2-image-captioning") model = AutoModelForImageTextToText.from_pretrained("nlpconnect/vit-gpt2-image-captioning") - Notebooks
- Google Colab
- Kaggle
Request: DOI
#11
by sasha - opened
I want to cite this model in a paper and would like a DOI to do so :)
Thanks @sasha
I have created DOI for this model.
@misc {nlp_connect_2022,
author = { {NLP Connect} },
title = { vit-gpt2-image-captioning (Revision 0e334c7) },
year = 2022,
url = { https://huggingface.co/nlpconnect/vit-gpt2-image-captioning },
doi = { 10.57967/hf/0222 },
publisher = { Hugging Face }
}