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@@ -6,34 +6,34 @@ comments: true
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## Latest Version Information
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## Latest Version Information
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-### PaddleX v3.0.0(5.20/2025)
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+### PaddleX v3.0.0(5.20/2025)
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Core upgrades are as follows:
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Core upgrades are as follows:
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-- **Rich Model Library:**
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- - **Extensive Model Coverage:** PaddleX 3.0 includes **270+ models**, covering diverse scenarios such as image/video classification/detection/segmentation, OCR, speech recognition, time series analysis, and more.
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- - **Mature Solutions:** Built on this robust model library, PaddleX 3.0 offers **critical and production-ready AI solutions**, including general document parsing, key information extraction, document understanding, table recognition, and general image recognition.
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-
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-- **Unified Inference API & Enhanced Deployment Capabilities:**
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- - **Standardized Inference Interface:** Reduces API fragmentation across model types, lowering the learning curve for users and accelerating enterprise adoption.
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- - **Multi-Model Composition:** Complex tasks can be efficiently tackled by combining different models, achieving synergistic performance (1+1>2).
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- - **Upgraded Deployment:** Unified commands now manage deployments for diverse models, supporting **multi-GPU inference** and **multi-instance serving deployments**.
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-
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-- **Full Compatibility with PaddlePaddle Framework 3.0:**
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- - **Leveraging New Paddle 3.0 Features:**
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- - Compiler-accelerated training: Enable by appending `-o Global.dy2st=True` to training commands. **Most GPU-based models see >10% speed gains, with some exceeding 30%.**
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- - Inference upgrades: Full adaptation to Paddle 3.0’s Program Intermediate Representation (PIR) enhances flexibility and compatibility. Static graph models now use `xxx.json` instead of `xxx.pdmodel`.
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- - **ONNX Model Support:** Seamless format conversion via the Paddle2ONNX plugin.
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-
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-- **Flagship Capabilities:**
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- - **PP-OCRv5:** Powers **multi-hardware inference, multi-backend support, and serving deployments** for this industry-leading OCR system.
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- - **PP-StructureV3:** Orchestrates **15+ models** in hybrid (serial/parallel) pipelines, achieving **SOTA accuracy on OmniDocBench**.
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- - **PP-ChatOCRv4:** Integrates with **PP-DocBee2 and ERNIE 4.5Turbo**, boosting key information extraction accuracy by **15.7 percentage points** over the previous generation.
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-
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-- **Multi-Hardware Support:**
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- - **Broad Compatibility:** Training and inference supported on **NVIDIA, Intel, Apple M-series, Kunlunxin, Ascend, Cambricon, Hygon, Enflame**, and more.
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- - **Ascend-Optimized:** **200+ fully adapted models**, including **21 OM-accelerated inference models**, plus key solutions like PP-OCRv5 and PP-StructureV3.
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- - **Kunlunxin-Optimized:** Critical classification, detection, and OCR models (including PP-OCRv5) are fully supported.
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|
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+- **Rich Model Library:**
|
|
|
|
|
+ - **Extensive Model Coverage:** PaddleX 3.0 includes **270+ models**, covering diverse scenarios such as image/video classification/detection/segmentation, OCR, speech recognition, time series analysis, and more.
|
|
|
|
|
+ - **Mature Solutions:** Built on this robust model library, PaddleX 3.0 offers **critical and production-ready AI solutions**, including general document parsing, key information extraction, document understanding, table recognition, and general image recognition.
|
|
|
|
|
+
|
|
|
|
|
+- **Unified Inference API & Enhanced Deployment Capabilities:**
|
|
|
|
|
+ - **Standardized Inference Interface:** Reduces API fragmentation across model types, lowering the learning curve for users and accelerating enterprise adoption.
|
|
|
|
|
+ - **Multi-Model Composition:** Complex tasks can be efficiently tackled by combining different models, achieving synergistic performance (1+1>2).
|
|
|
|
|
+ - **Upgraded Deployment:** Unified commands now manage deployments for diverse models, supporting **multi-GPU inference** and **multi-instance serving deployments**.
|
|
|
|
|
+
|
|
|
|
|
+- **Full Compatibility with PaddlePaddle Framework 3.0:**
|
|
|
|
|
+ - **Leveraging New Paddle 3.0 Features:**
|
|
|
|
|
+ - Compiler-accelerated training: Enable by appending `-o Global.dy2st=True` to training commands. **Most GPU-based models see >10% speed gains, with some exceeding 30%.**
|
|
|
|
|
+ - Inference upgrades: Full adaptation to Paddle 3.0’s Program Intermediate Representation (PIR) enhances flexibility and compatibility. Static graph models now use `xxx.json` instead of `xxx.pdmodel`.
|
|
|
|
|
+ - **ONNX Model Support:** Seamless format conversion via the Paddle2ONNX plugin.
|
|
|
|
|
+
|
|
|
|
|
+- **Flagship Capabilities:**
|
|
|
|
|
+ - **PP-OCRv5:** Powers **multi-hardware inference, multi-backend support, and serving deployments** for this industry-leading OCR system.
|
|
|
|
|
+ - **PP-StructureV3:** Orchestrates **15+ models** in hybrid (serial/parallel) pipelines, achieving **SOTA accuracy on OmniDocBench**.
|
|
|
|
|
+ - **PP-ChatOCRv4:** Integrates with **PP-DocBee2 and ERNIE 4.5Turbo**, boosting key information extraction accuracy by **15.7 percentage points** over the previous generation.
|
|
|
|
|
+
|
|
|
|
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+- **Multi-Hardware Support:**
|
|
|
|
|
+ - **Broad Compatibility:** Training and inference supported on **NVIDIA, Intel, Apple M-series, Kunlunxin, Ascend, Cambricon, Hygon, Enflame**, and more.
|
|
|
|
|
+ - **Ascend-Optimized:** **200+ fully adapted models**, including **21 OM-accelerated inference models**, plus key solutions like PP-OCRv5 and PP-StructureV3.
|
|
|
|
|
+ - **Kunlunxin-Optimized:** Critical classification, detection, and OCR models (including PP-OCRv5) are fully supported.
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### PaddleX v3.0.0rc1(4.22/2025)
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### PaddleX v3.0.0rc1(4.22/2025)
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