Model Details
Full Model IDmicrosoft/trocr-large-printed
Pipeline / Taskimage-to-text
Librarytransformers
Downloads (all-time)291.5K
Likes179
Last Modified5/27/2024
Author / Orgmicrosoft
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("image-to-text", model="microsoft/trocr-large-printed")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchsafetensorsvision-encoder-decoderimage-text-to-texttrocrimage-to-textarxiv:2109.10282endpoints_compatibleregion:us
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: image-to-text
This model is designed for the image-to-text task. Explore more models for this use case.
All image-to-text Models →📊 Popularity
⬇ Downloads291.5K
❤️ Community Likes179
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.