runtime error
Exit code: 1. Reason: /usr/local/lib/python3.10/site-packages/google/api_core/_python_version_support.py:275: FutureWarning: You are using a Python version (3.10.20) which Google will stop supporting in new releases of google.api_core once it reaches its end of life (2026-10-04). Please upgrade to the latest Python version, or at least Python 3.11, to continue receiving updates for google.api_core past that date. warnings.warn(message, FutureWarning) `torch_dtype` is deprecated! Use `dtype` instead! --- 袟袗袩校小袣 小袠小孝袝袦蝎 小 袩袨袛袛袝袪袞袣袨袡 袩袗袦携孝袠 --- Traceback (most recent call last): File "//app.py", line 23, in <module> model = AutoModelForCausalLM.from_pretrained( File "/usr/local/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py", line 374, in from_pretrained return model_class.from_pretrained( File "/usr/local/lib/python3.10/site-packages/transformers/modeling_utils.py", line 4118, in from_pretrained device_map = _get_device_map(model, device_map, max_memory, hf_quantizer) File "/usr/local/lib/python3.10/site-packages/transformers/integrations/accelerate.py", line 359, in _get_device_map hf_quantizer.validate_environment(device_map=device_map) File "/usr/local/lib/python3.10/site-packages/transformers/quantizers/quantizer_bnb_4bit.py", line 72, in validate_environment raise ValueError( ValueError: Some modules are dispatched on the CPU or the disk. Make sure you have enough GPU RAM to fit the quantized model. If you want to dispatch the model on the CPU or the disk while keeping these modules in 32-bit, you need to set `llm_int8_enable_fp32_cpu_offload=True` and pass a custom `device_map` to `from_pretrained`. Check https://huggingface.co/docs/transformers/main/en/main_classes/quantization#offload-between-cpu-and-gpu for more details.
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