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
Updates README.md sample running code to remove FutureWarning deprecation error for `ViTFeatureExtractor`.
#14
by commonslash - opened
Changes ViTFeatureExtractor to ViTFeatureExtractor in sample running code to resolve FutureWarning error: 'FutureWarning: The class ViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please use ViTImageProcessor instead.'
Thanks
ankur310794 changed pull request status to merged