ocr_big

xiaolv/ocr_big

Publisherxiaolv

Download access requirementsModelScope source

验证码识别模型 ocr-captcha专门识别常见验证码的模型，训练模型有2个： 1.small:训练数据大小为700MB，约8.4万张验证码图片，训练轮次27轮，最终的精度将近100%，推荐下载这个模型； 2.big:训练数据大小为11G，约135万个验证码图片，训练轮次1轮，最终的精度将近93.95%(由于资源问题，无法训练太久)；

Image Analysis

View all download instructions Mirror repository documentation and license ↗

Model details

模型介绍

中文整理

介绍（Introduction）

验证码识别模型 ocr-captcha**专门识别常见验证码的模型，训练模型有2个：

**small**:训练数据大小为700MB，约8.4万张验证码图片，训练轮次27轮，最终的精度将近100%，推荐下载这个模型；

**big**:训练数据大小为11G，约135万个验证码图片，训练轮次1轮，最终的精度将近93.95%(由于资源问题，无法训练太久)；

数据分布

**类型**：1. 纯数字型；2. 数字+字母型；3.纯字母型（大小写）

**长度**：4位、5位、6位

数据微调

**基座模型**：基座模型参考达摩院发布的读光-文字识别-行识别模型-中英-通用领域

**具体微调参考以上链接**

模型体验链接

modelscope：验证码识别模型（ocr-captcha）

快速使用（Quickstart）

代码提供web网页版：

详细数据参考huggingface代码：xiaolv/ocr-captcha

联系我们（Contact Us）

如果你想给我们的研发团队和产品团队留言，请通过邮件（2240560729@qq.com）联系我们。

优先采用原作者提供的中文模型卡片；仅有英文说明时由闲社AI翻译整理。重要参数、许可证和商用范围请以原文为准。

你将获得什么

完整仓库方式包含该固定版本中的权重、配置、分词器及说明文件；指定版本方式只下载所选文件或整组分片。多模态模型的投影文件、配置等依赖，请按作者说明配齐。

完整仓库可能包含多个权重格式，因此需要的磁盘空间可能大于单一格式的模型大小。下载文件不等于完成模型部署。

使用前须知

运行环境

运行模型需要的设备、工具与依赖，以原作者说明为准。

授权范围

是否允许商用、修改和分发，请查看模型许可证。

闲社提供资料与镜像下载方法，不代表已运行模型或完成安全审计。下载的代码应先检查，再执行。

Problem with the information or download?

Pinned version · Multiple download options

ocr_big model download

Download the full repository or choose a version or file.

Download tools · More than GGUF

Use the Hugging Face download tool to obtain xiaolv/ocr_big. Download Safetensors, GGUF, ONNX, configuration and other repository files. Downloading does not mean the tool can run this model.

Pinned-version file information is being completed. Existing downloads remain available, or load the file manifest below.

Choose a mirror or official source, your operating system and download scope below, then copy the command. Install the download tool first if needed.

Pinned version: c7b98979fc87e0d9bf4a4abfecbc025d459c5724. Downloads files only; does not start the model.

Choose a download source

Pinned ModelScope version: c7b98979fc87e0d9bf4a4abfecbc025d459c5724. Version identifiers can differ across sites. The alternative source was provided after checking weights and runtime configuration; this is not proof of a successful model run.

A checked, pinned ModelScope source is available for this model. Use the ModelScope download tool.

Choose what to download

Need just one GGUF precision? Load the file manifest and choose a version. Direct file links do not require Python; the command below can download multiple shards together.

Quantization / file

This reads the pinned version's file manifest; no model weights are downloaded.

Choose your operating system

For command-line downloads, follow these steps to get the full repository or selected files. Direct file links do not need these steps.

Open a terminal window

Create and open a folder for the model. In the folder's address bar, enter powershell and press Enter.

If Python is not installed, get it from the official Python website. In the terminal, enter python --version; continue when a version number appears.

First time? Install the download tool

Copy this command, paste it into the terminal, press Enter and wait for installation to finish.

python -m pip install --upgrade huggingface_hub

Already installed? Continue to step 3.

Run the download command

Select the button below, paste into the same terminal and press Enter. The tool downloads all files included in the current command.

Copying does not start a download. Paste and run the command on your device.

Where are the downloaded files?

Open the folder you chose. Look for the models folder. When progress stops and the terminal returns to its prompt without errors, check that all files are present. 'Copied' does not mean 'downloaded'.

No response or an error?

python not found: Install Python and reopen the terminal. On Windows, follow the installer's instructions to enable command-line access.

hf not found: Confirm that step 2 succeeded, then reopen the terminal. If needed, add Python's Scripts folder to your user PATH. Do not repeatedly download scripts.

Network interrupted: Stay in the same folder and run the same command again. The tool checks existing files.

Permission or disk error: Choose a writable folder with enough free space. Do not disable system security protection.

View the full download command

modelscope download --model "xiaolv/ocr_big" --revision "c7b98979fc87e0d9bf4a4abfecbc025d459c5724" --local_dir "./models/xiaolv--ocr_big--ms-c7b98979fc87"

Files transfer directly from the source you choose, not through Xianshe servers.

The version is pinned. Repeating the same command checks existing files. Change the source manually if it is slow or unavailable.

Public models do not require submitting keys to Xianshe. Restricted models still require the author's authorization. On Linux / macOS, use python3 instead of python when appropriate.