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MODEL Listed

TeleOCR

TeleOCR is an image-to-text model developed by XingChen-AGI on Hugging Face, offering developers a robust solution for extracting text from images. It's designed to handle various use cases, such as digitizing documents, extracting data from forms, and processing images in applications like OCR (Optical Character Recognition) pipelines. Its capabilities include recognizing text in different languages and fonts, making it versatile for international applications. For integration, it's built on standard frameworks, allowing easy embedding into existing software systems, whether through APIs or native code. Compared to other models, TeleOCR provides high accuracy with fewer parameters, reducing computational load and making it suitable for both mobile and web apps. Developers can leverage this for automating data entry, improving accessibility features in apps, or enhancing image processing workflows. Its 27,904 downloads and 739 likes on Hugging Face attest to its reliability and community adoption.

XingChen-AGIimage text to text
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01 / MODEL CARD

Model card

TeleOCR is an image-to-text model developed by XingChen-AGI on Hugging Face, offering developers a robust solution for extracting text from images. It's designed to handle various use cases, such as digitizing documents, extracting data from forms, and processing images in applications like OCR (Optical Character Recognition) pipelines. Its capabilities include recognizing text in different languages and fonts, making it versatile for international applications. For integration, it's built on standard frameworks, allowing easy embedding into existing software systems, whether through APIs or native code. Compared to other models, TeleOCR provides high accuracy with fewer parameters, reducing computational load and making it suitable for both mobile and web apps. Developers can leverage this for automating data entry, improving accessibility features in apps, or enhancing image processing workflows. Its 27,904 downloads and 739 likes on Hugging Face attest to its reliability and community adoption.

Model typeimage text to text
ProviderXingChen-AGI
Licenseapache-2.0
02 / FILES & VERSIONS

Model files and versions

Model cardModel description and metadata available in this entry
Listed
Source repositoryhttps://huggingface.co/XingChen-AGI/TeleOCR
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Version informationUse the source repository for the latest version
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03 / DOWNLOAD

Download this model

We recommend using the ModelScope CLI or SDK. Install ModelScope first, then choose a full snapshot, single file, SDK or Git LFS workflow.

This entry points to Hugging Face. The commands use the matching ModelScope repository format; confirm that the repository exists on ModelScope before running them. Model repository: XingChen-AGI/TeleOCR
Install ModelScope

Install the CLI and SDK dependency before downloading.

pip install modelscope
Download the full model repository

Download the complete weights, configuration and model card.

modelscope download --model XingChen-AGI/TeleOCR
Download one file to a local directory

README.md is used as an example; replace it with another repository file when needed.

modelscope download --model XingChen-AGI/TeleOCR README.md --local_dir ./dir
Download with the SDK

Useful in Python projects and automation scripts.

from modelscope import snapshot_download
model_dir = snapshot_download('XingChen-AGI/TeleOCR')
Clone with Git

Make sure Git LFS is installed correctly.

git lfs install
git clone https://www.modelscope.cn/XingChen-AGI/TeleOCR.git
Clone without downloading LFS blobs

Fetch the repository structure first, then pull large files when needed.

GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/XingChen-AGI/TeleOCR.git
04 / WORKFLOW

How to use

  1. 01
    Step 1

    Read the model card and source information.

  2. 02
    Step 2

    Start with a small, non-sensitive evaluation.

  3. 03
    Step 3

    Review quality, licensing and usage limits.

  4. 04
    Step 4

    Adopt it only after validation.

05 / DISCUSSIONS

Discussions

Use this space to keep checking source information, usage experience and maintenance status.

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