Image Classification
Transformers
PyTorch
English
vision-encoder-decoder
image-text-to-text
image-captioning
Instructions to use deepklarity/poster2plot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepklarity/poster2plot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="deepklarity/poster2plot") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("deepklarity/poster2plot") model = AutoModelForMultimodalLM.from_pretrained("deepklarity/poster2plot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 123d7c4c65762d55c4717ec833cb38b0d46fa5e8474314c83533744653f51f55
- Size of remote file:
- 982 MB
- SHA256:
- 052d52744f8e1f51fe14b6c512965d3ab1498f35761e1839f9b12875a70a8a8a
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