run-locally-issues

[Aliktk]

@Asma-Alkhaldi need help to run the repo locally.

I am trying it to setup it installed everything.
During clonning the Llama-2-7b-chat-hf is it important to clone inside the repo or outside? or should I only download the checkpoints and give path in the llama_model: "/miniGPT-Med/llama-2-7b-chat-hf"?

also share ur tips for this?
Can I run it without GPU? I have limited setup for now.

Thank you for your help

I tried w/o cloning llama7b:

(miniGPT-Med) D:\All Projects\MiniGPT-Med>python demo_v2.py --cfg-path eval_configs/minigptv2_eval.yaml --gpu-id 0

===================================BUG REPORT===================================
Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues
================================================================================
CUDA SETUP: Required library version not found: libsbitsandbytes_cpu.so. Maybe you need to compile it from source?
CUDA SETUP: Defaulting to libbitsandbytes_cpu.so...
argument of type 'WindowsPath' is not iterable
C:\Users\Nawaz\anaconda3\envs\miniGPT-Med\lib\site-packages\bitsandbytes\cextension.py:31: UserWarning: The installed version of bitsandbytes was compiled without GPU support. 8-bit optimizers and GPU quantization are unavailable.
  warn("The installed version of bitsandbytes was compiled without GPU support. "
Initializing Chat
Traceback (most recent call last):
  File "D:\All Projects\MiniGPT-Med\demo_v2.py", line 63, in <module>
    model = model_cls.from_config(model_config).to(device)
  File "D:\All Projects\MiniGPT-Med\minigpt4\models\minigpt_v2.py", line 114, in from_config
    model = cls(
  File "D:\All Projects\MiniGPT-Med\minigpt4\models\minigpt_v2.py", line 46, in __init__
    super().__init__(
  File "D:\All Projects\MiniGPT-Med\minigpt4\models\minigpt_base.py", line 41, in __init__
    self.llama_model, self.llama_tokenizer = self.init_llm(
  File "D:\All Projects\MiniGPT-Med\minigpt4\models\base_model.py", line 174, in init_llm
    llama_tokenizer = LlamaTokenizer.from_pretrained(llama_model_path, use_fast=False)
  File "C:\Users\Nawaz\anaconda3\envs\miniGPT-Med\lib\site-packages\transformers\tokenization_utils_base.py", line 1784, in from_pretrained   
    resolved_vocab_files[file_id] = cached_file(
  File "C:\Users\Nawaz\anaconda3\envs\miniGPT-Med\lib\site-packages\transformers\utils\hub.py", line 417, in cached_file
    resolved_file = hf_hub_download(
  File "C:\Users\Nawaz\anaconda3\envs\miniGPT-Med\lib\site-packages\huggingface_hub\utils\_validators.py", line 110, in _inner_fn
    validate_repo_id(arg_value)
  File "C:\Users\Nawaz\anaconda3\envs\miniGPT-Med\lib\site-packages\huggingface_hub\utils\_validators.py", line 158, in validate_repo_id      
    raise HFValidationError(
huggingface_hub.utils._validators.HFValidationError: Repo id must be in the form 'repo_name' or 'namespace/repo_name': '/miniGPT-Med/llama-2-7b-chat-hf'. Use `repo_type` argument if needed.