Instructions to use microsoft/trocr-base-printed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/trocr-base-printed 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="microsoft/trocr-base-printed")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("microsoft/trocr-base-printed") model = AutoModelForImageTextToText.from_pretrained("microsoft/trocr-base-printed") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 04627a9a9f34f70963a8e7275be8aa7bf14a0e40349531afd5fc3072c37ea90b
- Size of remote file:
- 1.33 GB
- SHA256:
- a67665277b31df7da142e76e5247d2f464d9914cd5ccf7edaf83c1e79547a130
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.