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@mohiso22 can you fix the quickcheck pls? |
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April 7, 2026 09:29
Signed-off-by: Mohit Soni <mohisoni@qti.qualcomm.com>
Signed-off-by: Mohit Soni <mohisoni@qti.qualcomm.com>
vbaddi
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Apr 7, 2026
examples/image_text_to_text/models/qwen2_5_vl/multi_specialization_inference.py
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April 8, 2026 11:16
Signed-off-by: Mohit Soni <mohisoni@qti.qualcomm.com>
Signed-off-by: Mohit Soni <mohisoni@qti.qualcomm.com>
quic-rishinr
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Apr 8, 2026
examples/image_text_to_text/models/qwen_vl/multi_specialization_inference.py
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| def _generate_multi_frame_specialization( | ||
| self, | ||
| inputs: List[str] = None, |
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nit: update the type annotation for inputs as inputs: Dict[str, torch.Tensor]
QEfficient/transformers/models/qwen2_5_vl/modeling_qwen2_5_vl.py
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April 9, 2026 09:28
Signed-off-by: Mohit Soni <mohisoni@qti.qualcomm.com>
Signed-off-by: Mohit Soni <mohisoni@qti.qualcomm.com>
Signed-off-by: Mohit Soni <mohisoni@qti.qualcomm.com>
Signed-off-by: Mohit Soni <mohisoni@qti.qualcomm.com>
Signed-off-by: Mohit Soni <mohisoni@qti.qualcomm.com>
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Adds multi-specialization support for Qwen2.5-VL and Qwen3-VL, enabling the vision encoder to be compiled with multiple resolution configurations (height/width/num_frames as lists) in one shot.
Introduces a dedicated _generate_multi_frame_specialization inference path that selects the right specialization at runtime, along with example scripts for both model families.