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anmol-unitmole
/
image-caption-generation-vision-encoder-decoder-model

Image-to-Text
Transformers
ONNX
Transformers.js
PyTorch
English
vision-encoder-decoder
image-text-to-text
image-captioning
vision-language
onnxruntime
vit
gpt2
Model card Files Files and versions
xet
Community

Instructions to use anmol-unitmole/image-caption-generation-vision-encoder-decoder-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use anmol-unitmole/image-caption-generation-vision-encoder-decoder-model 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="anmol-unitmole/image-caption-generation-vision-encoder-decoder-model")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMultimodalLM
    
    tokenizer = AutoTokenizer.from_pretrained("anmol-unitmole/image-caption-generation-vision-encoder-decoder-model")
    model = AutoModelForMultimodalLM.from_pretrained("anmol-unitmole/image-caption-generation-vision-encoder-decoder-model", device_map="auto")
  • Transformers.js

    How to use anmol-unitmole/image-caption-generation-vision-encoder-decoder-model with Transformers.js:

    // npm i @huggingface/transformers
    import { pipeline } from '@huggingface/transformers';
    
    // Allocate pipeline
    const pipe = await pipeline('image-to-text', 'anmol-unitmole/image-caption-generation-vision-encoder-decoder-model');
  • Notebooks
  • Google Colab
  • Kaggle
image-caption-generation-vision-encoder-decoder-model
1.01 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
anmol-unitmole's picture
anmol-unitmole
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  • README.md
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  • config.json
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  • generation_config.json
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  • merges.txt
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  • preprocessor_config.json
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  • special_tokens_map.json
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  • tokenizer.json
    3.56 MB
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  • tokenizer_config.json
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  • vocab.json
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