update

README.md

@@ -44,7 +44,7 @@ PaddleOCR-VL: Boosting Multilingual Document Parsing via a 0.9B Ultra-Compact Vi
 </div>
 
 <div align="center">
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/allmetric.png" width="800"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/allmetric.png" width="800"/>
 </div>
 
 ## Introduction
@@ -67,12 +67,13 @@ PaddleOCR-VL: Boosting Multilingual Document Parsing via a 0.9B Ultra-Compact Vi
 <!-- PaddleOCR-VL decomposes the complex task of document parsing into a two stages. The first stage, PP-DocLayoutV2, is responsible for layout analysis, where it localizes semantic regions and predicts their reading order. Subsequently, the second stage, PaddleOCR-VL-0.9B, leverages these layout predictions to perform fine-grained recognition of diverse content, including text, tables, formulas, and charts. Finally, a lightweight post-processing module aggregates the outputs from both stages and formats the final document into structured Markdown and JSON. -->
 
 <div align="center">
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/paddleocrvl.png" width="800"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/paddleocrvl.png" width="800"/>
 </div>
 
 
 ## News 
 * ```2025.10.16``` 🚀 We release [PaddleOCR-VL](https://github.com/PaddlePaddle/PaddleOCR), — a multilingual documents parsing via a 0.9B Ultra-Compact Vision-Language Model with SOTA performance.
+* ```2025.10.29``` Supports calling the core module PaddleOCR-VL-0.9B of PaddleOCR-VL via the `transformers` library.
 
 
 ## Usage    
@@ -140,6 +141,59 @@ for res in output:
     ```
   
 **For more usage details and parameter explanations, see the [documentation](https://www.paddleocr.ai/latest/en/version3.x/pipeline_usage/PaddleOCR-VL.html).**
+
+## PaddleOCR-VL-0.9B Usage with transformers
+
+Currently, we support inference using the PaddleOCR-VL-0.9B model with the `transformers` library, which can recognize texts, formulas, tables, and chart elements. In the future, we plan to support full document parsing inference with `transformers`. Below is a simple script we provide to support inference using the PaddleOCR-VL-0.9B model with `transformers`. 
+
+> [!NOTE]
+> Note: We currently recommend using the official method for inference, as it is faster and supports page-level document parsing. The example code below only supports element-level recognition.
+
+```python
+from PIL import Image
+import torch
+from transformers import AutoModelForCausalLM, AutoProcessor
+
+DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
+
+CHOSEN_TASK = "ocr"  # Options: 'ocr' | 'table' | 'chart' | 'formula'
+PROMPTS = {
+    "ocr": "OCR:",
+    "table": "Table Recognition:",
+    "formula": "Formula Recognition:",
+    "chart": "Chart Recognition:",
+}
+
+model_path = "PaddlePaddle/PaddleOCR-VL"
+image_path = "test.png"
+image = Image.open(image_path).convert("RGB")
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_path, trust_remote_code=True, torch_dtype=torch.bfloat16
+).to(DEVICE).eval()
+processor = AutoProcessor.from_pretrained(model_path, trust_remote_code=True)
+
+messages = [
+    {"role": "user",         
+     "content": [
+            {"type": "image", "image": image},
+            {"type": "text", "text": PROMPTS[CHOSEN_TASK]},
+        ]
+    }
+]
+inputs = processor.apply_chat_template(
+    messages, 
+    tokenize=True, 
+    add_generation_prompt=True, 	
+    return_dict=True,
+	return_tensors="pt"
+).to(DEVICE)
+
+outputs = model.generate(**inputs, max_new_tokens=1024)
+outputs = processor.batch_decode(outputs, skip_special_tokens=True)[0]
+print(outputs)
+```
+
 ## Performance
 
 ### Page-Level Document Parsing 
@@ -150,7 +204,7 @@ for res in output:
 ##### PaddleOCR-VL achieves SOTA performance for overall, text, formula, tables and reading order on OmniDocBench v1.5
 
 <div align="center">
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/omni15.png" width="800"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/omni15.png" width="800"/>
 </div>
 
 
@@ -161,7 +215,7 @@ for res in output:
 
 
 <div align="center">
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/omni10.png" width="800"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/omni10.png" width="800"/>
 </div>
 
 
@@ -178,7 +232,7 @@ for res in output:
 PaddleOCR-VL’s robust and versatile capability in handling diverse document types, establishing it as the leading method in the OmniDocBench-OCR-block performance evaluation. 
 
 <div align="center">
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/omnibenchocr.png" width="800"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/omnibenchocr.png" width="800"/>
 </div>
 
 
@@ -187,7 +241,7 @@ PaddleOCR-VL’s robust and versatile capability in handling diverse document ty
 In-house-OCR provides a evaluation of performance across multiple languages and text types. Our model demonstrates outstanding accuracy with the lowest edit distances in all evaluated scripts.
 
 <div align="center">
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/inhouseocr.png" width="800"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/inhouseocr.png" width="800"/>
 </div>
 
 
@@ -199,7 +253,7 @@ In-house-OCR provides a evaluation of performance across multiple languages and
 Our self-built evaluation set contains diverse types of table images, such as Chinese, English, mixed Chinese-English, and tables with various characteristics like full, partial, or no borders, book/manual formats, lists, academic papers, merged cells, as well as low-quality, watermarked, etc. PaddleOCR-VL achieves remarkable performance across all categories.
 
 <div align="center">
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/inhousetable.png" width="600"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/inhousetable.png" width="600"/>
 </div>
 
 #### 3. Formula
@@ -209,7 +263,7 @@ Our self-built evaluation set contains diverse types of table images, such as Ch
 In-house-Formula evaluation set contains simple prints, complex prints, camera scans, and handwritten formulas. PaddleOCR-VL demonstrates the best performance in every category.
 
 <div align="center">
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/inhouse-formula.png" width="500"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/inhouse-formula.png" width="500"/>
 </div>
 
 
@@ -220,7 +274,7 @@ In-house-Formula evaluation set contains simple prints, complex prints, camera s
 The evaluation set is broadly categorized into 11 chart categories, including bar-line hybrid, pie, 100% stacked bar, area, bar, bubble, histogram, line, scatterplot, stacked area, and stacked bar. PaddleOCR-VL not only outperforms expert OCR VLMs but also surpasses some 72B-level multimodal language models.
 
 <div align="center">
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/inhousechart.png" width="400"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/inhousechart.png" width="400"/>
 </div>
 
 
@@ -235,42 +289,42 @@ The evaluation set is broadly categorized into 11 chart categories, including ba
 ### Comprehensive Document Parsing
 
 <div align="center">
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/overview1.jpg" width="600"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/overview1.jpg" width="600"/>
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/overview2.jpg" width="600"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/overview2.jpg" width="600"/>
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/overview3.jpg" width="600"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/overview3.jpg" width="600"/>
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/overview4.jpg" width="600"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/overview4.jpg" width="600"/>
 </div>
 
 
 ### Text
 
 <div align="center">
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/text_english_arabic.jpg" width="300" style="display: inline-block;"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/text_english_arabic.jpg" width="300" style="display: inline-block;"/>
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/text_handwriting_02.jpg" width="300" style="display: inline-block;"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/text_handwriting_02.jpg" width="300" style="display: inline-block;"/>
 </div>
 
 
 ### Table
 
 <div align="center">
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/table_01.jpg" width="300" style="display: inline-block;"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/table_01.jpg" width="300" style="display: inline-block;"/>
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/table_02.jpg" width="300" style="display: inline-block;"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/table_02.jpg" width="300" style="display: inline-block;"/>
 </div>
 
 
 ### Formula
 
 <div align="center">
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/formula_EN.jpg" width="300" style="display: inline-block;"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/formula_EN.jpg" width="300" style="display: inline-block;"/>
-<img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/formula_ZH.jpg" width="300" style="display: inline-block;"/>
+<img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/formula_ZH.jpg" width="300" style="display: inline-block;"/>
 </div>
 
 
 ### Chart
 
 <div align="center">
-  <img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/chart_01.jpg" width="300" style="display: inline-block;"/>
+  <img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/chart_01.jpg" width="300" style="display: inline-block;"/>
-  <img src="https://modelscope.cn/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/master/imgs/chart_02.jpg" width="300" style="display: inline-block;"/>
+  <img src="https://huggingface.co/datasets/PaddlePaddle/PaddleOCR-VL_demo/resolve/main/imgs/chart_02.jpg" width="300" style="display: inline-block;"/>
 </div>
 
 

chat_template.jinja

@@ -7,14 +7,38 @@
 {%- if not sep_token is defined -%}
     {%- set sep_token = "<|end_of_sentence|>" -%}
 {%- endif -%}
+{%- if not image_token is defined -%}
+    {%- set image_token = "<|IMAGE_START|><|IMAGE_PLACEHOLDER|><|IMAGE_END|>" -%}
+{%- endif -%}
 {{- cls_token -}}
 {%- for message in messages -%}
     {%- if message["role"] == "user" -%}
-        {{- "User: <|IMAGE_START|><|IMAGE_PLACEHOLDER|><|IMAGE_END|>" + message["content"] + "\n" -}}
+        {{- "User: " -}}
+        {%- for content in message["content"] -%}
+            {%- if content["type"] == "image" -%}
+                {{ image_token }}
+            {%- endif -%}
+        {%- endfor -%}
+        {%- for content in message["content"] -%}
+            {%- if content["type"] == "text" -%}
+                {{ content["text"] }}
+            {%- endif -%}
+        {%- endfor -%}
+        {{ "\n" -}}
     {%- elif message["role"] == "assistant" -%}
-        {{- "Assistant: " + message["content"] + sep_token -}}
+        {{- "Assistant: " -}}
+        {%- for content in message["content"] -%}
+            {%- if content["type"] == "text" -%}
+                {{ content["text"] + "\n" }}
+            {%- endif -%}
+        {%- endfor -%}
+        {{ sep_token -}}
     {%- elif message["role"] == "system" -%}
-        {{- message["content"] -}}
+        {%- for content in message["content"] -%}
+            {%- if content["type"] == "text" -%}
+                {{ content["text"] + "\n" }}
+            {%- endif -%}
+        {%- endfor -%}
     {%- endif -%}
 {%- endfor -%}
 {%- if add_generation_prompt -%}