Image-to-Text
Transformers
PyTorch
Safetensors
vision-encoder-decoder
image-text-to-text
image-captioning
Instructions to use AIris-Channel/vit-gpt2-verifycode-caption with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AIris-Channel/vit-gpt2-verifycode-caption 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="AIris-Channel/vit-gpt2-verifycode-caption")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("AIris-Channel/vit-gpt2-verifycode-caption") model = AutoModelForMultimodalLM.from_pretrained("AIris-Channel/vit-gpt2-verifycode-caption") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 814124e63a2fd1a92dccd097c3bf48675fe69115be5419e96590f2ed11b1d27f
- Size of remote file:
- 957 MB
- SHA256:
- 12fde92ad7047f4dc316ce88e0a922b872d7b3db12bbb61e60f9de17ada6f201
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