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```CODE:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="MiniMaxAI/MiniMax-M2")
messages = [
{"role": "user", "content": "Who are you?"},
]
pipe(messages)
```
ERROR:
Traceback (most recent call last):
File "/tmp/MiniMaxAI_MiniMax-M2_0AY8pTg.py", line 17, in <module>
pipe = pipeline("text-generation", model="MiniMaxAI/MiniMax-M2")
File "/tmp/.cache/uv/environments-v2/d3eea229ed2fb556/lib/python3.13/site-packages/transformers/pipelines/__init__.py", line 1027, in pipeline
framework, model = infer_framework_load_model(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
adapter_path if adapter_path is not None else model,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
...<5 lines>...
**model_kwargs,
^^^^^^^^^^^^^^^
)
^
File "/tmp/.cache/uv/environments-v2/d3eea229ed2fb556/lib/python3.13/site-packages/transformers/pipelines/base.py", line 333, in infer_framework_load_model
raise ValueError(
f"Could not load model {model} with any of the following classes: {class_tuple}. See the original errors:\n\n{error}\n"
)
ValueError: Could not load model MiniMaxAI/MiniMax-M2 with any of the following classes: (<class 'transformers.models.auto.modeling_auto.AutoModelForCausalLM'>,). See the original errors:
while loading with AutoModelForCausalLM, an error is thrown:
Traceback (most recent call last):
File "/tmp/.cache/uv/environments-v2/d3eea229ed2fb556/lib/python3.13/site-packages/transformers/pipelines/base.py", line 293, in infer_framework_load_model
model = model_class.from_pretrained(model, **kwargs)
File "/tmp/.cache/uv/environments-v2/d3eea229ed2fb556/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/d3eea229ed2fb556/lib/python3.13/site-packages/transformers/modeling_utils.py", line 277, in _wrapper
return func(*args, **kwargs)
File "/tmp/.cache/uv/environments-v2/d3eea229ed2fb556/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/d3eea229ed2fb556/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/d3eea229ed2fb556/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.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/tmp/.cache/uv/environments-v2/d3eea229ed2fb556/lib/python3.13/site-packages/transformers/pipelines/base.py", line 311, in infer_framework_load_model
model = model_class.from_pretrained(model, **fp32_kwargs)
File "/tmp/.cache/uv/environments-v2/d3eea229ed2fb556/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/d3eea229ed2fb556/lib/python3.13/site-packages/transformers/modeling_utils.py", line 277, in _wrapper
return func(*args, **kwargs)
File "/tmp/.cache/uv/environments-v2/d3eea229ed2fb556/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/d3eea229ed2fb556/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/d3eea229ed2fb556/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.
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