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PaddleOCR-VL

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from paddleocr import PaddleOCRVL
pipeline = PaddleOCRVL(device="cpu")
output = pipeline.predict("https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/paddleocr_vl_demo.png")

Creating model: ('PP-DocLayoutV2', None)
Model files already exist. Using cached files. To redownload, please delete the directory manually: `/.paddlex/official_models/PP-DocLayoutV2`.
Creating model: ('PaddleOCR-VL-0.9B', None)
Model files already exist. Using cached files. To redownload, please delete the directory manually: `/.paddlex/official_models/PaddleOCR-VL`.
Loading configuration file /.paddlex/official_models/PaddleOCR-VL/config.json
Loading weights file /.paddlex/official_models/PaddleOCR-VL/model.safetensors
use GQA - num_heads: 16- num_key_value_heads: 2
use GQA - num_heads: 16- num_key_value_heads: 2
use GQA - num_heads: 16- num_key_value_heads: 2
use GQA - num_heads: 16- num_key_value_heads: 2
use GQA - num_heads: 16- num_key_value_heads: 2
use GQA - num_heads: 16- num_key_value_heads: 2
use GQA - num_heads: 16- num_key_value_heads: 2
use GQA - num_heads: 16- num_key_value_heads: 2
use GQA - num_heads: 16- num_key_value_heads: 2
use GQA - num_heads: 16- num_key_value_heads: 2
use GQA - num_heads: 16- num_key_value_heads: 2
use GQA - num_heads: 16- num_key_value_heads: 2
use GQA - num_heads: 16- num_key_value_heads: 2
use GQA - num_heads: 16- num_key_value_heads: 2
use GQA - num_heads: 16- num_key_value_heads: 2
use GQA - num_heads: 16- num_key_value_heads: 2
use GQA - num_heads: 16- num_key_value_heads: 2
use GQA - num_heads: 16- num_key_value_heads: 2
Loaded weights file from disk, setting weights to model.
All model checkpoint weights were used when initializing PaddleOCRVLForConditionalGeneration.
...
Currently, the PaddleOCR-VL-0.9B local model only supports batch size of 1. The batch size will be updated to 1.
Connecting to https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/paddleocr_vl_demo.png ...
Downloading paddleocr_vl_demo.png ...
[==================================================] 100.00%

Error:

RuntimeError                              Traceback (most recent call last)
Cell In[9], line 3
      1 from paddleocr import PaddleOCRVL
      2 pipeline = PaddleOCRVL(device="cpu")
----> 3 output = pipeline.predict("https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/paddleocr_vl_demo.png")
      4 for res in output:
      5     res.print()

File ~/.venv/lib/python3.13/site-packages/paddleocr/_pipelines/paddleocr_vl.py:134, in PaddleOCRVL.predict(self, input, use_doc_orientation_classify, use_doc_unwarping, use_layout_detection, use_chart_recognition, layout_threshold, layout_nms, layout_unclip_ratio, layout_merge_bboxes_mode, use_queues, prompt_label, format_block_content, repetition_penalty, temperature, top_p, min_pixels, max_pixels, **kwargs)
    112 def predict(
    113     self,
    114     input,
   (...)    132     **kwargs,
    133 ):
--> 134     return list(
    135         self.predict_iter(
    136             input,
    137             use_doc_orientation_classify=use_doc_orientation_classify,
    138             use_doc_unwarping=use_doc_unwarping,
    139             use_layout_detection=use_layout_detection,
    140             use_chart_recognition=use_chart_recognition,
    141             layout_threshold=layout_threshold,
    142             layout_nms=layout_nms,
    143             layout_unclip_ratio=layout_unclip_ratio,
...
    675     )
    676 else:
    677     yield item[1]

RuntimeError: Exception from the 'vlm' worker: Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' 'truncation=True' to have batched tensors with the same length.