runtime error

Exit code: 1. Reason: Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads. Loading luvGPT/deepseek-uncensored-lore... Fetching 6 files: 0%| | 0/6 [00:00<?, ?it/s] Fetching 6 files: 17%|█▋ | 1/6 [00:41<03:29, 41.96s/it] Fetching 6 files: 33%|███▎ | 2/6 [00:42<01:11, 17.75s/it] Fetching 6 files: 83%|████████▎ | 5/6 [00:43<00:05, 5.23s/it] Fetching 6 files: 100%|██████████| 6/6 [00:43<00:00, 7.26s/it] Traceback (most recent call last): File "/app/app.py", line 13, in <module> model = AutoModelForCausalLM.from_pretrained( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py", line 387, in from_pretrained return model_class.from_pretrained( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/transformers/modeling_utils.py", line 4113, in from_pretrained device_map = _get_device_map(model, device_map, max_memory, hf_quantizer) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/transformers/integrations/accelerate.py", line 373, in _get_device_map hf_quantizer.validate_environment(device_map=device_map) File "/usr/local/lib/python3.11/site-packages/transformers/quantizers/quantizer_bnb_8bit.py", line 74, 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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