import torch
from transformers import Qwen2_5_VLForConditionalGeneration, AutoProcessor

num_beams = 2
do_sample = False
max_token_length = 8192
video_path = 'some video file path'

# load model
model_id = 'Qwen/Qwen2.5-VL-7B-Instruct'
model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
    model_id,
    torch_dtype=torch.float16,
    device_map='auto',
)
processor = AutoProcessor.from_pretrained(model_id)

messages = []
messages.append({
        "role": "user",
        "content": [
            {"type": "text", "text": 'Describe a video in detail.'},
            {"type": "video", "path": video_path},
        ],
})

inputs = processor.apply_chat_template(
    messages,
    add_generation_prompt=True,
    tokenize=True,
    return_dict=True,
    return_tensors="pt"
).to(model.device, dtype=model.dtype)

if num_beams > 1:
    inp_model_kwargs = {'num_beams': num_beams}
else:
    inp_model_kwargs = {}

outputs = model.generate(
    **inputs,
    do_sample=do_sample,
    max_new_tokens=max_token_length,
    **inp_model_kwargs
    # num_return_sequences=2,
)
# ...

Traceback (most recent call last):
  File "hf_vlm_run_exps_eval.py", line 750, in <module>
    run_main()
  File "hf_vlm_run_exps_eval.py", line 734, in run_main
    answers_dict = exec_llm_on_segment_videos(
  File "hf_vlm_run_exps_eval.py", line 473, in exec_llm_on_segment_videos
    output_text = extract_answer_from_llm(
  File "hf_vlm_run_exps_eval.py", line 517, in extract_answer_from_llm
    output_text = hf_base_model_wrapper.run_model_single_inference(
  File "hf_base_model_wrapper.py", line 94, in run_model_single_inference
    outputs = model.generate(
  File "C:\Users\User\.conda\envs\env_grounded_sam2\lib\site-packages\torch\utils\_contextlib.py", line 116, in decorate_context
    return func(*args, **kwargs)
  File "C:\Users\User\.conda\envs\env_grounded_sam2\lib\site-packages\transformers\generation\utils.py", line 2637, in generate
    input_ids, model_kwargs = self._expand_inputs_for_generation(
  File "C:\Users\User\.conda\envs\env_grounded_sam2\lib\site-packages\transformers\models\qwen2_5_vl\modeling_qwen2_5_vl.py", line 1695, in _expand_inputs_for_generation
    model_kwargs = _expand_dict_for_generation_visual(model_kwargs)
  File "C:\Users\User\.conda\envs\env_grounded_sam2\lib\site-packages\transformers\models\qwen2_5_vl\modeling_qwen2_5_vl.py", line 1672, in _expand_dict_for_generation_visual
    raise TypeError(
TypeError: Expected value for key 'second_per_grid_ts' to be a list, but got <class 'torch.Tensor'> instead.