code_execution_files / Qwen_Qwen3-VL-32B-Instruct-FP8_1.txt
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```CODE:
# Load model directly
from transformers import AutoProcessor, AutoModelForVision2Seq
processor = AutoProcessor.from_pretrained("Qwen/Qwen3-VL-32B-Instruct-FP8")
model = AutoModelForVision2Seq.from_pretrained("Qwen/Qwen3-VL-32B-Instruct-FP8")
messages = [
{
"role": "user",
"content": [
{"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
{"type": "text", "text": "What animal is on the candy?"}
]
},
]
inputs = processor.apply_chat_template(
messages,
add_generation_prompt=True,
tokenize=True,
return_dict=True,
return_tensors="pt",
).to(model.device)
outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
```
ERROR:
Traceback (most recent call last):
File "/tmp/Qwen_Qwen3-VL-32B-Instruct-FP8_1slct1n.py", line 20, in <module>
model = AutoModelForVision2Seq.from_pretrained("Qwen/Qwen3-VL-32B-Instruct-FP8")
File "/tmp/.cache/uv/environments-v2/3a120645d4f704f5/lib/python3.13/site-packages/transformers/models/auto/modeling_auto.py", line 2289, in from_pretrained
return super().from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/tmp/.cache/uv/environments-v2/3a120645d4f704f5/lib/python3.13/site-packages/transformers/models/auto/auto_factory.py", line 604, in from_pretrained
return model_class.from_pretrained(
~~~~~~~~~~~~~~~~~~~~~~~~~~~^
pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/tmp/.cache/uv/environments-v2/3a120645d4f704f5/lib/python3.13/site-packages/transformers/modeling_utils.py", line 277, in _wrapper
return func(*args, **kwargs)
File "/tmp/.cache/uv/environments-v2/3a120645d4f704f5/lib/python3.13/site-packages/transformers/modeling_utils.py", line 4881, in from_pretrained
hf_quantizer, config, dtype, device_map = get_hf_quantizer(
~~~~~~~~~~~~~~~~^
config, quantization_config, dtype, from_tf, from_flax, device_map, weights_only, user_agent
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/tmp/.cache/uv/environments-v2/3a120645d4f704f5/lib/python3.13/site-packages/transformers/quantizers/auto.py", line 319, in get_hf_quantizer
hf_quantizer.validate_environment(
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
dtype=dtype,
^^^^^^^^^^^^
...<3 lines>...
weights_only=weights_only,
^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/tmp/.cache/uv/environments-v2/3a120645d4f704f5/lib/python3.13/site-packages/transformers/quantizers/quantizer_finegrained_fp8.py", line 48, in validate_environment
raise RuntimeError("No GPU or XPU found. A GPU or XPU is needed for FP8 quantization.")
RuntimeError: No GPU or XPU found. A GPU or XPU is needed for FP8 quantization.