Image-to-Text
Transformers
PyTorch
Safetensors
vision-encoder-decoder
image-text-to-text
image-captioning
Instructions to use bipin/image-caption-generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bipin/image-caption-generator 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="bipin/image-caption-generator")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("bipin/image-caption-generator") model = AutoModelForImageTextToText.from_pretrained("bipin/image-caption-generator") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c4c6be003750b46f46bf8d1595a09ff75f0124fce6a789143c90258cf56297e
- Size of remote file:
- 982 MB
- SHA256:
- d244e567d52fa4d18dd799325a104bf3de772550d2cb8dc16c58e7784a0a53bf
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