software-mansion/react-native-executorch-pp-ocrv6

🤗 Hugging Face 来源image-to-textapache-2.0216 MBother✓ 4 个校验和今天更新
一条命令提交

在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对,然后提交。你只需开始做种,并粘贴你账户中的密钥。它只读取你的文件,绝不修改。如果愿意,可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo software-mansion/react-native-executorch-pp-ocrv6 ./model-folder
需要做种者 →

pp-ocrv6

This repository hosts the pp-ocrv6 models exported for the React Native ExecuTorch library as ExecuTorch .pte programs, ready to run on device.

Upstream models:

Variants

Path Backend Precision
coreml/pp_ocrv6_coreml_int8.pte coreml int8
vulkan/pp_ocrv6_vulkan_fp16.pte vulkan fp16
xnnpack/pp_ocrv6_xnnpack_fp32.pte xnnpack fp32
xnnpack/pp_ocrv6_xnnpack_int8.pte xnnpack int8

Repository structure

charset.json                       128 kB
config.json                        30 B
coreml/config.json                 1.3 kB
coreml/pp_ocrv6_coreml_int8.pte    7.9 MB
vulkan/config.json                 1.3 kB
vulkan/pp_ocrv6_vulkan_fp16.pte    25.0 MB
xnnpack/config.json                2.3 kB
xnnpack/pp_ocrv6_xnnpack_fp32.pte  29.6 MB
xnnpack/pp_ocrv6_xnnpack_int8.pte  22.8 MB

Compatibility

These files are published for the ExecuTorch v1.4.1 runtime. ExecuTorch gives no forward compatibility guarantee, so an older runtime may fail to load them.

To use them in React Native ExecuTorch, pass the model constant shipped in the library's model registry to the corresponding task pipeline. See the documentation.

To load these files in your own ExecuTorch runtime, read the compatibility note first.

CoreML notes (iOS)

  • The CoreML .pte is a multifunction Core ML model (detect + recognize share one precompiled .mlmodelc). Requires iOS 18+ and an ExecuTorch runtime ≥ 1.3 (multifunction loading via functionName).
  • First-ever load on a device triggers a one-time per-shape ANE specialization (OS-cached afterwards) — warm each model once after install.

Model details

The recognizer's output is a probability distribution over the charset with softmax already baked in. Index 0 is the CTC blank, so charset[i] corresponds to logit i + 1.