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, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("AIris-Channel/vit-gpt2-verifycode-caption") model = AutoModelForImageTextToText.from_pretrained("AIris-Channel/vit-gpt2-verifycode-caption") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a8ddeb9987e27182808854f2b05c4896da5342ec5462b6e719f895184870a47
- Size of remote file:
- 4.03 kB
- SHA256:
- 400e34fa29e864cff77d3c48a0f3c9eedb3d68ef1e8b908b07d2333e4d43fa9f
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