dont support CohereForAI/c4ai-command-r-plus-4bit

[valueLzy]

Some weights of the model checkpoint at CohereForAI/c4ai-command-r-plus-4bit were not used when initializing CohereForCausalLM: ['model.layers.0.self_attn.k_norm.weight', 'model.layers.0.self_attn.q_norm.weight', 'model.layers.1.self_attn.k_norm.weight', 'model.layers.1.self_attn.q_norm.weight', 'model.layers.10.self_attn.k_norm.weight', 'model.layers.10.self_attn.q_norm.weight', 'model.layers.11.self_attn.k_norm.weight', 'model.layers.11.self_attn.q_norm.weight', 'model.layers.12.self_attn.k_norm.weight', 'model.layers.12.self_attn.q_norm.weight', 'model.layers.13.self_attn.k_norm.weight', 'model.layers.13.self_attn.q_norm.weight', 'model.layers.14.self_attn.k_norm.weight', 'model.layers.14.self_attn.q_norm.weight', 'model.layers.15.self_attn.k_norm.weight', 'model.layers.15.self_attn.q_norm.weight', 'model.layers.16.self_attn.k_norm.weight', 'model.layers.16.self_attn.q_norm.weight', 'model.layers.17.self_attn.k_norm.weight', 'model.layers.17.self_attn.q_norm.weight', 'model.layers.18.self_attn.k_norm.weight', 'model.layers.18.self_attn.q_norm.weight', 'model.layers.19.self_attn.k_norm.weight', 'model.layers.19.self_attn.q_norm.weight', 'model.layers.2.self_attn.k_norm.weight', 'model.layers.2.self_attn.q_norm.weight', 'model.layers.20.self_attn.k_norm.weight', 'model.layers.20.self_attn.q_norm.weight', 'model.layers.21.self_attn.k_norm.weight', 'model.layers.21.self_attn.q_norm.weight', 'model.layers.22.self_attn.k_norm.weight', 'model.layers.22.self_attn.q_norm.weight', 'model.layers.23.self_attn.k_norm.weight', 'model.layers.23.self_attn.q_norm.weight', 'model.layers.24.self_attn.k_norm.weight', 'model.layers.24.self_attn.q_norm.weight', 'model.layers.25.self_attn.k_norm.weight', 'model.layers.25.self_attn.q_norm.weight', 'model.layers.26.self_attn.k_norm.weight', 'model.layers.26.self_attn.q_norm.weight', 'model.layers.27.self_attn.k_norm.weight', 'model.layers.27.self_attn.q_norm.weight', 'model.layers.28.self_attn.k_norm.weight', 'model.layers.28.self_attn.q_norm.weight', 'model.layers.29.self_attn.k_norm.weight', 'model.layers.29.self_attn.q_norm.weight', 'model.layers.3.self_attn.k_norm.weight', 'model.layers.3.self_attn.q_norm.weight', 'model.layers.30.self_attn.k_norm.weight', 'model.layers.30.self_attn.q_norm.weight', 'model.layers.31.self_attn.k_norm.weight', 'model.layers.31.self_attn.q_norm.weight', 'model.layers.32.self_attn.k_norm.weight', 'model.layers.32.self_attn.q_norm.weight', 'model.layers.33.self_attn.k_norm.weight', 'model.layers.33.self_attn.q_norm.weight', 'model.layers.34.self_attn.k_norm.weight', 'model.layers.34.self_attn.q_norm.weight', 'model.layers.35.self_attn.k_norm.weight', 'model.layers.35.self_attn.q_norm.weight', 'model.layers.36.self_attn.k_norm.weight', 'model.layers.36.self_attn.q_norm.weight', 'model.layers.37.self_attn.k_norm.weight', 'model.layers.37.self_attn.q_norm.weight', 'model.layers.38.self_attn.k_norm.weight', 'model.layers.38.self_attn.q_norm.weight', 'model.layers.39.self_attn.k_norm.weight', 'model.layers.39.self_attn.q_norm.weight', 'model.layers.4.self_attn.k_norm.weight', 'model.layers.4.self_attn.q_norm.weight', 'model.layers.40.self_attn.k_norm.weight', 'model.layers.40.self_attn.q_norm.weight', 'model.layers.41.self_attn.k_norm.weight', 'model.layers.41.self_attn.q_norm.weight', 'model.layers.42.self_attn.k_norm.weight', 'model.layers.42.self_attn.q_norm.weight', 'model.layers.43.self_attn.k_norm.weight', 'model.layers.43.self_attn.q_norm.weight', 'model.layers.44.self_attn.k_norm.weight', 'model.layers.44.self_attn.q_norm.weight', 'model.layers.45.self_attn.k_norm.weight', 'model.layers.45.self_attn.q_norm.weight', 'model.layers.46.self_attn.k_norm.weight', 'model.layers.46.self_attn.q_norm.weight', 'model.layers.47.self_attn.k_norm.weight', 'model.layers.47.self_attn.q_norm.weight', 'model.layers.48.self_attn.k_norm.weight', 'model.layers.48.self_attn.q_norm.weight', 'model.layers.49.self_attn.k_norm.weight', 'model.layers.49.self_attn.q_norm.weight', 'model.layers.5.self_attn.k_norm.weight', 'model.layers.5.self_attn.q_norm.weight', 'model.layers.50.self_attn.k_norm.weight', 'model.layers.50.self_attn.q_norm.weight', 'model.layers.51.self_attn.k_norm.weight', 'model.layers.51.self_attn.q_norm.weight', 'model.layers.52.self_attn.k_norm.weight', 'model.layers.52.self_attn.q_norm.weight', 'model.layers.53.self_attn.k_norm.weight', 'model.layers.53.self_attn.q_norm.weight', 'model.layers.54.self_attn.k_norm.weight', 'model.layers.54.self_attn.q_norm.weight', 'model.layers.55.self_attn.k_norm.weight', 'model.layers.55.self_attn.q_norm.weight', 'model.layers.56.self_attn.k_norm.weight', 'model.layers.56.self_attn.q_norm.weight', 'model.layers.57.self_attn.k_norm.weight', 'model.layers.57.self_attn.q_norm.weight', 'model.layers.58.self_attn.k_norm.weight', 'model.layers.58.self_attn.q_norm.weight', 'model.layers.59.self_attn.k_norm.weight', 'model.layers.59.self_attn.q_norm.weight', 'model.layers.6.self_attn.k_norm.weight', 'model.layers.6.self_attn.q_norm.weight', 'model.layers.60.self_attn.k_norm.weight', 'model.layers.60.self_attn.q_norm.weight', 'model.layers.61.self_attn.k_norm.weight', 'model.layers.61.self_attn.q_norm.weight', 'model.layers.62.self_attn.k_norm.weight', 'model.layers.62.self_attn.q_norm.weight', 'model.layers.63.self_attn.k_norm.weight', 'model.layers.63.self_attn.q_norm.weight', 'model.layers.7.self_attn.k_norm.weight', 'model.layers.7.self_attn.q_norm.weight', 'model.layers.8.self_attn.k_norm.weight', 'model.layers.8.self_attn.q_norm.weight', 'model.layers.9.self_attn.k_norm.weight', 'model.layers.9.self_attn.q_norm.weight']

• This IS expected if you are initializing CohereForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
• This IS NOT expected if you are initializing CohereForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model). 2024-04-16 11:23:21 | WARNING | accelerate.big_modeling | You shouldn't move a model that is dispatched using accelerate hooks. 2024-04-16 11:23:21 | ERROR | stderr | Traceback (most recent call last): 2024-04-16 11:23:21 | ERROR | stderr | File "/usr/lib/python3.9/runpy.py", line 197, in _run_module_as_main 2024-04-16 11:23:21 | ERROR | stderr | return _run_code(code, main_globals, None, 2024-04-16 11:23:21 | ERROR | stderr | File "/usr/lib/python3.9/runpy.py", line 87, in _run_code 2024-04-16 11:23:21 | ERROR | stderr | exec(code, run_globals) 2024-04-16 11:23:21 | ERROR | stderr | File "/opt/FastChat/fastchat/serve/model_worker.py", line 414, in 2024-04-16 11:23:21 | ERROR | stderr | args, worker = create_model_worker() 2024-04-16 11:23:21 | ERROR | stderr | File "/opt/FastChat/fastchat/serve/model_worker.py", line 385, in create_model_worker 2024-04-16 11:23:21 | ERROR | stderr | worker = ModelWorker( 2024-04-16 11:23:21 | ERROR | stderr | File "/opt/FastChat/fastchat/serve/model_worker.py", line 77, in init 2024-04-16 11:23:21 | ERROR | stderr | self.model, self.tokenizer = load_model( 2024-04-16 11:23:21 | ERROR | stderr | File "/opt/FastChat/fastchat/model/model_adapter.py", line 376, in load_model 2024-04-16 11:23:21 | ERROR | stderr | model.to(device) 2024-04-16 11:23:21 | ERROR | stderr | File "/usr/local/lib/python3.9/dist-packages/accelerate/big_modeling.py", line 456, in wrapper 2024-04-16 11:23:21 | ERROR | stderr | return fn(*args, **kwargs) 2024-04-16 11:23:21 | ERROR | stderr | File "/usr/local/lib/python3.9/dist-packages/transformers/modeling_utils.py", line 2554, in to 2024-04-16 11:23:21 | ERROR | stderr | raise ValueError( 2024-04-16 11:23:21 | ERROR | stderr | ValueError: .to is not supported for 4-bit or 8-bit bitsandbytes models. Please use the model as it is, since the model has already been set to the correct devices and casted to the correct dtype

[White-Friday]

Could you please explain how you specify the --conv-template?