runtime error

Exit code: 1. Reason: �██████| 47.6k/47.6k [00:00<00:00, 129MB/s] tokenizer.json: 0%| | 0.00/20.1M [00:00<?, ?B/s] tokenizer.json: 100%|██████████| 20.1M/20.1M [00:00<00:00, 35.4MB/s] special_tokens_map.json: 0%| | 0.00/577 [00:00<?, ?B/s] special_tokens_map.json: 100%|██████████| 577/577 [00:00<00:00, 4.77MB/s] config.json: 0%| | 0.00/1.53k [00:00<?, ?B/s] config.json: 100%|██████████| 1.53k/1.53k [00:00<00:00, 9.43MB/s] /usr/local/lib/python3.10/site-packages/transformers/quantizers/auto.py:206: UserWarning: You passed `quantization_config` or equivalent parameters to `from_pretrained` but the model you're loading already has a `quantization_config` attribute. The `quantization_config` from the model will be used. warnings.warn(warning_msg) Traceback (most recent call last): File "/home/user/app/app.py", line 37, in <module> model = AutoModelForCausalLM.from_pretrained( File "/usr/local/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py", line 564, in from_pretrained return model_class.from_pretrained( File "/usr/local/lib/python3.10/site-packages/transformers/modeling_utils.py", line 262, in _wrapper return func(*args, **kwargs) File "/usr/local/lib/python3.10/site-packages/transformers/modeling_utils.py", line 3698, in from_pretrained hf_quantizer.validate_environment( File "/usr/local/lib/python3.10/site-packages/transformers/quantizers/quantizer_bnb_4bit.py", line 103, 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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